Autoplay
Autocomplete
Previous Lesson
Complete and Continue
Build Your Own Personal Assistant with AutoGPT and ChatGPT
Mammoth Interactive Courses Introduction
00 About Mammoth Interactive (1:12)
01 How To Learn Online Effectively (13:46)
Source Files
00 Welcome to the Auto-GPT Masterclass
00 Welcome to the Auto-GPT Masterclass (4:30)
ChatGPT 4 AI Prompt Engineering for Entrepreneurs
00-01 Introduction Of The Instructor (2:25)
01 01 What Is Chatgpt (7:50)
01 02 Intro To Prompt Engineering-Prompt Types (8:28)
01 03 Intro To Prompt Engineering-Effective Prompts (8:41)
01B 01 Project Preview (2:04)
01B 02A Simplify Complex Information (8:38)
01B 02B Simplify Complex Information-Other Strategies (8:41)
02 03 Proofread-Email And Business Proposals (8:39)
02.03 Proofread-More Use Cases (8:24)
02.04 Re-Organize Data-Benefits And First Sample Use Case (6:22)
02.04 Re-Organize Data-Potential Use Cases Case (10:44)
02.05 Work With Spreadsheets-Automating Data Entry (7:46)
02.05 Work With Spreadsheets-Formulas And Other Use Cases (7:31)
03 01 Project Preview (1:23)
03.02 Create Content (4:03)
03.03 Social Media (4:26)
03.04 Write Ad Copy (8:17)
03.05 Write Email Marketing Campaigns (4:55)
03.06 Write An Outreach Message (5:08)
03.07 Copyrighting (4:29)
03.08 Seo (5:09)
03.09 Video Scripts (8:49)
03.10 Generate Text In Your Writing Style (3:25)
04 01 Project Preview (1:51)
04.02 Research-Chatgpt Usecase And Benefits (7:05)
04.02 Research-More Examples And Explanation (7:49)
04.03 Write An Article-Add Role To Chatgpt (7:17)
04.03 Write An Article-Generate High Quality Content (8:02)
04.04 Check Plagiarism (10:56)
04.05 Prepare For Job Opportunities-Cv And Cover Letter (8:28)
04.05 Prepare For Job Opportunities-Interview Questions, Connection And Task Generator (8:36)
05 01 Project Preview (2:33)
05.02 Generate Code-Javascript And Python Code Snippets (9:26)
05.02 Generate Code-Stylesheet, Html, C++ And Conversion (9:20)
05.03 Build Algorithms-Algorithm To Pseudocode (4:03)
05.03 Build Algorithms-Realworld Use Cases (8:11)
05.04 Debug-Python Use Case (6:51)
05.04 Debug-React, Api, Javascript, Html And Css (6:56)
05.05 Write Code Documentation (9:51)
05.06 Use Chatgpt As A Linux Terminal (8:32)
05.07 Use Chatgpt As A Unix Terminal (9:08)
05.08 Use Chatgpt As A Microsoft Dos Terminal (5:28)
05.09 Use Chatgpt To Suggest Uxui Designs (8:10)
05.10 Use Chatgpt To Suggest Cybersecurity Solutions (10:05)
Source Files
00b What is Auto-GPT
01 What is Auto-GPT (2:47)
02 What you need to run Auto-GPT (4:01)
Source Files - Auto-GPT
02 Install Prerequisites - 01 Install Git
01 What Is Git (3:00)
02 Install Git On Mac (4:06)
03 Update Git On Mac (3:56)
04 Install Git On Windows (3:20)
Source files
02 Install Prerequisites - 02 Install Python
02 Install Python (2:43)
02 Install Prerequisites - 03 (Prerequisite) Command Line Fundamentals
01 Why All Developers Need To Know The Command Line (8:50)
03 What Are Linux And Unix Terminals (8:04)
01 What You-ll Need (1:20)
02 Install Linux Command Line On Windows (3:18)
01 Build Your First Command In The Command Line (3:48)
02 Navigate Directories In The Command Line (6:33)
03 Build And Edit A New File In The Command Line (7:27)
04 Move Files In The Command Line (9:00)
03 Install Auto-GPT
01 Install Auto-GPT (5:44)
02 Configure Auto-GPT with OpenAI API key (5:02)
Source fIles
04 Run Auto-GPT with the Command Line
01 Run Auto-GPT to automate your first task (12:59)
02 Auto build and write document with Auto-GPT (13:20)
03 Clean text file with Auto-GPT (6:37)
Source
05 Research, summarize and save with Auto-GPT
01 Search the web with Auto-GPT (5:17)
02 Research, summarize and save with Auto-GPT (10:02)
Source
06a Project Prerequisites - 01 (Prerequisite) Install Node and NPM
02 Install Yarn On Mac (4:22)
01 What Is Yarn (2:16)
06a Project Prerequisites - 02 (Prerequisite) Introduction to React
00 Why You Should Learn React (5:30)
01 React Introduction (12:33)
02 Set up a Container (8:13)
03 Generate a List (6:46)
04 Add Items to the List (6:34)
05 Clear Input Field (10:26)
06 Remove a Task (10:39)
Source Files
06 Web development with Auto-GPT and React JS
01 Build a website with Auto-GPT (9:47)
02 Build a React project with Auto-GPT (6:20)
Source
07 Automate copywriting with Auto-GPT
01 Scrape site and improve product description with Chat-GPT (16:28)
Source Files
08 Improve Auto-GPT results with plugins
01 Enable plugins in Auto-GPT (9:30)
02 How Auto-GPT plugins work (5:55)
Source Files
(Prerequisite) Introduction to Python
00. Introduction (4:42)
02. Variables (19:17)
03. Type Conversion Examples (10:04)
04. Operators (7:04)
05. Operators Examples (21:52)
06. Collections (8:23)
07. Lists (11:38)
08. Multidimensional List Examples (8:05)
09. Tuples Examples (8:34)
10. Dictionaries Examples (14:24)
11. Ranges Examples (8:30)
12. Conditionals (6:41)
13. If Statement Examples (10:16)
14. If Statement Variants Examples (11:18)
15. Loops (7:00)
16. While Loops Examples (11:30)
17. For Loops Examples (11:18)
18. Functions (7:47)
19. Functions Examples (9:16)
20. Parameters And Return Values Examples (13:46)
21. Classes And Objects (11:13)
22. Classes Example (13:11)
23. Objects Examples (9:54)
24. Inheritance Examples (17:26)
25. Static Members Example (11:03)
26. Summary And Outro (4:06)
09 Use third party plugin in Auto-GPT
01 Inject OS system into Auto-GPT with System Info Plugin (3:50)
02 Use System Info Plugin in Auto-GPT (2:33)
Source Files
10 Automate Twitter with Auto-GPT
01 Generate Twitter consumer key, access token and client ID (3:50)
02 Auto post to Twitter with Auto-GPT (4:16)
03 Automate replying to Tweets with Auto-GPT (2:12)
04 Auto read tweets with Auto-GPT (3:27)
Source Files
11 Write detailed image descriptions with Auto-GPT and SceneX
00 What is SceneX Auto-GPT plugin (3:50)
01 Write detailed image descriptions with Auto-GPT and SceneX (5:49)
Source
12 Automate email with Auto-GPT
01 Make app password for gmail automation (1:25)
02 Configure Auto-GPT for email automation (4:08)
03 Send email with Auto-GPT (10:07)
04 Read and respond to emails with Auto-GPT (6:40)
Source
13 Automate Excel files with Auto-GPT
01 Generate spreadsheet data with Auto-GPT (6:52)
02 Format Excel spreadsheet with Auto-GPT (21:44)
03 Manipulate data in Excel sheets with Auto-GPT (8:23)
04 Replace data in Excel spreadsheet with Auto-GPT (9:23)
05 Prevent data repetition in Excel with Auto-GPT (15:29)
Source
14 Web scraping with Excel and Auto-GPT
01 Scrape web and save data in Excel file with Auto-GPT (15:59)
02 Remove whitespace from Excel file with Auto-GPT (4:34)
Source
15 Build web app with AI interaction in Python
01 Show ChatGPT answers in HTML with Python (12:24)
02 Improve ChatGPT API response (3:41)
Source
16 Build ChatGPT Web UI with Flask and Auto-GPT
01 Generate Python Flask web app with Auto-GPT (7:32)
02 Run Python web app with Flask (5:35)
03 Send prompt from Python web app to ChatGPT (7:02)
04 Test POST request from Python web app to ChatGPT (7:46)
05 Show ChatGPT responses on Python Flask web app (6:20)
06 Test sending ChatGPT response to custom web app (6:47)
07 Show all ChatGPT messages in Flask (5:01)
08 Test Auto-GPT code with virtual environment (4:53)
Source
17 Style webpage with Auto-GPT and Bootstrap
01 Style webpage with Auto-GPT and Bootstrap (8:08)
02 Test web style built with Auto-GPT (7:16)
Source
18 Build AI vs AI chat app with Auto-GPT and Flask
01 Send POST requests to Flask app with Python (8:03)
02 Handle JSON POST request data in Flask (10:21)
03 Auto generate prompts with ChatGPT and Python (14:02)
04 Auto refresh Flask app with HTML (4:31)
05 Add personality and character to ChatGPT bots (8:23)
Source
19 Set Up Google Cloud and Python with Auto-GPT
00 Set up Google Cloud project (2:13)
01 Install libraries with pip (1:30)
02 Connect to Google Calendar API with Auto-GPT and Python (8:38)
03 Configure redirect URL and test users in Google Cloud (5:01)
04 Fetch Google Calendar events and Python (7:45)
Source
20 Generate web app with form in Auto-GPT
01 Generate web app with form in Auto-GPT (6:17)
02 Configure web app for Calendar (8:54)
Source
21 Connect ChatGPT to Google Calendar with Python
01 Extract datetime from chat message with ChatGPT (10:12)
02 Create custom Google Calendar event with Python (7:08)
03 Add Bootstrap style and Calendar embed (7:33)
Source
22 Build a Hello World Auto-GPT Plugin
01 Download Auto-GPT Plugins (4:19)
02 Build a Hello World Auto-GPT Plugin (11:44)
03 Use custom plugin with Auto-GPT (2:06)
04 Build Unit Tests for Auto-GPT Plugin (5:46)
Source
23 Build Auto-GPT Plugin for Google Calendar
02 Generate service token for Google API credentials
01 Build first party plugin template in Auto-GPT (4:26)
03 Connect to Google Calendar API in Auto-GPT Plugin (5:40)
04 Hide private data with environment variables (8:55)
Source
24 Get upcoming events in Calendar Auto-GPT Plugin
02 Test get upcoming events in Auto-GPT (8:12)
01 Get upcoming events with Google Calendar API (7:25)
Source
25 Create Google Calendar event in custom Auto-GPT plugin
02 Create Calendar event with Auto-GPT (10:48)
01 Create Google Calendar event in custom Auto-GPT plugin (4:45)
Source
Code Python on the Web
02.01 What is Google Colab (4:24)
02.02 What If I Get Errors (2:40)
02.03 How Do I Terminate a Session (2:40)
Mastering the chatGPT OpenAI API
00b-01 Openai Api Models To Work With (2:53)
00b-02 How Openai Api Works (2:09)
00b-03 Adjust Openai Api Model Parameters (7:58)
01-01 Use Openai Api To Answer Questions Like Chatgtp (10:19)
01-02 Correct Grammar With Openai Api (3:30)
01-03 Summarize And Simplify Text With Openai Api (4:03)
01-04 Translate Text With Openai Api (3:04)
02-01 Generate Code With Openai Api (7:11)
02-02 Explain Code With Openai Api (5:24)
02-03 Calculate Time Complexity With Openai Api (3:40)
02-04 Translate Programming Languages With OpenAI API (4:24)
02-05 Fix Bugs In Code With Openai Api (3:19)
03-01 Generate Sql Queries With Openai Py (5:15)
03-02 Build Structured Table Data From Long Form Text (4:29)
03-03 Classify Items Into Categories With Openai Api (4:50)
03-04 Generate Spreadsheets And Lists With Chatgpt Openai Api (5:46)
04-01 Convert Notes To Summary With Openai Api (5:40)
04-02 Add Emotional Sentiment To Text With Openai Models (9:40)
04-03 Generate Questions On A Topic With Gpt Turbo (9:26)
04-04 Generate Text Conversation With Chatgpt Api (5:19)
05-01 Classify Text Emotion Sentiment With Chatgpt Models (5:09)
05-02 Extract Keywords From Text With Chatgpt Api (4:31)
05-03 Convert Product Description To Ad With Chatgpt Python (3:57)
05-04 Generate Product Names With Chatgpt In Python (4:04)
05-05 Extract Information From Text With Chatgpt Api (2:57)
06-01 Build Html Parser With Python (4:31)
06-02 Scrape Hyperlinks From Url Webpage With Python (4:09)
06-03 Filter Out Urls Not Part Of Domain (7:03)
06-04 Save Web Content To Files With Python (10:07)
07-01 Convert Text To Csv With Python (6:36)
07-02 Remove Whitespace And Lines From Text With Python (4:58)
07-03 Tokenize Text With Python For Machine Learning Models (2:50)
07-04 Split Long Lines With Python (4:11)
07-05 Split Pandas Dataframe Into Sections With Python (7:19)
07-06 Embed Text For Machine Learning With Openai Api (8:05)
08-01 Embed Question With Python (5:48)
08-02 Answer Questions About Your Data With Customized Openai Model (10:36)
09-01 Load And Read Pdf In Python (3:40)
09-02 Build Vector Index From Pdf Text In Python (4:32)
09-03 Answer Questions About Pdf With Chatgpt Model In Python (5:10)
10-01 Generate Review Data With Chatgpt Api (8:14)
10-02 Format Python Text To Multidimensional Pandas Dataframe (11:50)
10-03 Change Column Data Type In Pandas Dataframe (2:40)
10-04 Embed Text Data With Openai Api (6:25)
Source files
Auto-GPT Fundamentals - Installation Requirements - Git
01 What Is Git (3:00)
02 Install Git On Mac (4:06)
03 Update Git On Mac (3:56)
04 Install Git On Windows (3:20)
Source files
Auto-GPT Fundamentals - Installation Requirements - Python
02 Install Python (2:43)
Auto-GPT Fundamentals - Installation Requirements - Command Line Fundamentals
01-01 Why All Developers Need To Know The Command Line (8:50)
01-02 What Are Linux And Unix Terminals (8:04)
02-01 What You-ll Need (1:20)
02-02 Install Linux Command Line On Windows (3:18)
03-01 Build Your First Command In The Command Line (3:48)
03-02 Navigate Directories In The Command Line (6:33)
03-03 Build And Edit A New File In The Command Line (7:27)
03-04 Move Files In The Command Line (9:00)
Source Files
Auto-GPT Fundamentals - Installation Requirements - Install Node and NPM
00 What Is Node JS (8:22)
02 Install Yarn On Mac (4:22)
01 What Is Yarn (2:16)
02 How to Install Node and NPM on Windows-R (8:41)
Source files
Auto-GPT Fundamentals - Installation Requirements - Introduction to React
00 Why You Should Learn React (5:30)
01 React Introduction (12:33)
02 Set up a Container (8:13)
03 Generate a List (6:46)
04 Add Items to the List (6:34)
05 Clear Input Field (10:26)
06 Remove a Task (10:39)
Source Files
Auto-GPT Fundamentals - 01 Getting Started with Auto-GPT_ ChatGPT for the Computer
00b-01 What Is Auto-GPT (2:53)
00b-02 What You Need To Run Auto-Gpt (4:07)
03-01 Install Auto-GPT_1 (5:50)
03-02 Configure Auto-Gpt With Openai Api Key (5:07)
04-01 Run Auto-Gpt To Automate Your First Task (13:05)
04-02 Auto Build And Write Document With Auto-Gpt (13:26)
04-03 Clean Text File With Auto-Gpt (6:42)
05-01 Search The Web With Auto-Gpt (5:23)
05-02 Research, Summarize And Save With Auto-Gpt (10:08)
06B-01 Build A Website With Auto-Gpt (9:53)
06B-02 Build A React Project With Auto-GPT (6:26)
07-01 Scrape Site And Improve Product Description With Chat-GPT (16:34)
Source Files
Auto-GPT Fundamentals - Install curl (for Mac or Linux Unix Terminals only)
01 Install Curl (3:32)
Auto-GPT Fundamentals - 02 Automate Web Tasks with Auto-GPT Plugins
08-01 Enable Plugins In Auto-GPT (9:35)
08-02 How Auto-Gpt Plugins Work (6:01)
09-01 Inject Os System Into Auto-GPT With System Info Plugin (3:55)
09-02 Use System Info Plugin In Auto-GPT (2:38)
10-01 Generate Twitter Consumer Key, Access Token And Client ID (3:55)
10-02 Auto Post To Twitter With Auto-Gpt (4:21)
10-03 Automate Replying To Tweets With Auto-GPT (2:17)
10-04 Auto Read Tweets With Auto-Gpt (3:33)
11-00 What Is Scenex Auto-GPT Plugin (3:56)
11-01 Write Detailed Image Descriptions With Auto-Gpt And Scenex (5:55)
12-01 Make App Password For Gmail Automation (1:31)
12-02 Configure Auto-Gpt For Email Automation (4:13)
12-03 Send Email With Auto-Gpt (10:13)
12-04 Read And Respond To Emails With Auto-GPT (6:45)
Source Files
Auto-GPT Fundamentals - 03 Automate Excel Files with Auto-GPT
02 Format Excel Spreadsheet (21:49)
01 Generate Spreadsheet Data (6:58)
03 Manipulate Data In Excel Sheets With (8:28)
04 Replace Data In Excel Spreadsheet (9:28)
05 Prevent Data Repetition In Excel (15:35)
Source
Auto-GPT Fundamentals - (Prerequisite) HTML Fundamentals
00 How To Become A Web Developer (7:40)
01 HTML Basics (7:26)
02 CSS Basics (5:50)
03 Add Images To Website With HTML (9:13)
04 Link To Pages With HTML Hyperlinks (5:30)
05 Positioning Items On A Webpage With CSS Flexbox (11:32)
06 Spacing Out Items With Flexbox (9:31)
Auto-GPT Fundamentals - Introduction to Python (Prerequisite)
02.01 What is Google Colab (4:24)
00. Introduction (4:42)
02.02 What If I Get Errors (2:40)
02.03 How Do I Terminate a Session (2:40)
02. Variables (19:17)
03. Type Conversion Examples (10:04)
04. Operators (7:04)
05. Operators Examples (21:52)
06. Collections (8:23)
07. Lists (11:38)
08. Multidimensional List Examples (8:05)
09. Tuples Examples (8:34)
10. Dictionaries Examples (14:24)
11. Ranges Examples (8:30)
12. Conditionals (6:41)
13. If Statement Examples (10:16)
14. If Statement Variants Examples (11:18)
15. Loops (7:00)
16. While Loops Examples (11:30)
17. For Loops Examples (11:18)
18. Functions (7:47)
19. Functions Examples (9:16)
20. Parameters And Return Values Examples (13:46)
21. Classes And Objects (11:13)
22. Classes Example (13:11)
23. Objects Examples (9:54)
24. Inheritance Examples (17:26)
25. Static Members Example (11:03)
26. Summary And Outro (4:06)
Source code
Auto-GPT Fundamentals - 04 Automate Python Web Scraping and Development with Auto-GPT
14b-01 Scrape Web And Save Data In Excel File With Auto-Gpt_1 (16:04)
14b-02 Remove Whitespace From Excel File With Auto-Gpt (4:40)
15b-01 Show Chatgpt Answers In Html With Python (12:30)
15b-02 Improve Chatgpt API Response (3:46)
Source files
Auto-GPT Fundamentals - Project Prerequisites
01 Build Your First Flask App (13:26)
02 Render HTML On Multiple Pages (10:53)
03 Build Page Templates With HTML (9:31)
04 Build Dynamic Page Templates (5:36)
05 Display JSON Data (5:21)
06 Build A Template To Show All Data (9:16)
Source Files
01 What Is Http (5:35)
02 Http Request Types (5:55)
03 Elements Of Http Requests And Responses (4:19)
Source Code
Auto-GPT Fundamentals - 05 Build ChatGPT Web UI Clones
16-01 Generate Python Flask Web App With Auto-GPT (7:38)
16-02 Run Python Web App With Flask (5:41)
16-03 Send Prompt From Python Web App To Chatgpt (7:07)
16-04 Test Post Request From Python Web App To Chatgpt (7:51)
16-05 Show Chatgpt Responses On Python Flask Web App (6:26)
16-06 Test Sending Chatgpt Response To Custom Web App (6:52)
16-07 Show All Chatgpt Messages In Flask (5:07)
16-08 Test Auto-Gpt Code With Virtual Environment (4:58)
17-01 Style Webpage With Auto-GPT And Bootstrap (8:13)
17-02 Test Web Style Built With Auto-GPT (7:22)
18-01 Send Post Requests To Flask App With Python (8:09)
18-02 Handle Json Post Request Data In Flask (10:27)
18-03 Auto Generate Prompts With Chatgpt And Python (14:07)
18-04 Auto Refresh Flask App With Html (4:36)
18-05 Add Personality And Character To Chatgpt Bots (8:28)
Source Files
Auto-GPT Fundamentals - 06 Integrate ChatGPT into Google Calendar
01 Generate Web App With Form In Auto-GPT (6:23)
02 Configure Web App For Calendar (8:59)
19-00 Set Up Google Cloud Project (2:19)
19-01 Install Libraries With Pip (1:36)
19-02 Connect To Google Calendar Api With Auto-Gpt And Python (8:44)
19-03 Configure Redirect Url And Test Users In Google Cloud (5:06)
19-04 Fetch Google Calendar Events And Python (7:51)
21-01 Extract Datetime From Chat Message With ChatGPT (10:18)
21-02 Create Custom Google Calendar Event With Python (7:13)
21-03 Add Bootstrap Style And Calendar Embed (7:39)
Source Files
Auto-GPT Fundamentals - 07 Build Custom Plugins for Auto-GPT
22-01 Download Auto-Gpt Plugins (4:25)
22-02 Build A Hello World Auto-Gpt Plugin (11:49)
22-03 Use Custom Plugin With Auto-Gpt (2:12)
22-04 Build Unit Tests For Auto-Gpt Plugin (5:51)
23-01 Build First Party Plugin Template In Auto-GPT (4:31)
23-03 Connect To Google Calendar Api In Auto-Gpt Plugin (5:46)
23-04 Hide Private Data With Environment Variables (9:01)
24-01 Get Upcoming Events With Google Calendar API (7:30)
24-02 Test Get Upcoming Events In Auto-Gpt (8:18)
25-01 Create Google Calendar Event In Custom Auto-GPT Plugin (4:51)
25-02 Create Calendar Event With Auto-Gpt (10:54)
Source Files
ChatGPT 4 Prompt Engineering for Finance and Stock Market Investing
01.01 Course Requirement_1 (3:20)
02 01 Project Preview_1 (2:03)
02 02A Analyze Financial Statements Of Stock (9:00)
02 02B Financial Ratio And Trend Analysis (4:25)
02 03 Balance Sheet, Income Statement And Cash Flow Statement (9:00)
02 04 Loopholes And Weaknesses In Stock Financials (8:39)
02 05 Analyze Historical Stock Performance (11:16)
02 06 Predict Stock Performance (5:08)
02 07 Market Share_1 (5:31)
02 08 Industry Analysis (7:48)
02 09 Management Team Analysis (8:25)
02 10 Analyze Stock Risks (6:56)
02 11 Valuation (8:11)
02 12 Explain Business Model Of A Company (6:24)
02 13 Perform A Swot Analysis (8:16)
02 14 Summarize A Company’S Earnings Report Calls (6:55)
02 15 Evaluate A Company’S Esg Credentials (4:39)
03 01 Project Preview_1 (0:48)
03 02A Invest Short Term (6:22)
03 02B Implementing Your Short-Term Investment Strategy (8:06)
03 03A Invest Long Term (5:58)
03 03B Analyzing The Results (7:27)
03 04A Using Chatgpt To Assess Your Risk Tolerance (7:32)
03 04B Customized Investment Recommendations Based On Individual Financial Goals And Risk Tolerance (5:26)
03 04C Implementing Your Customized Investment Plan (8:47)
04 01 Project Preview_1 (1:25)
04.02A Recent Past Stock Market State (7:44)
04.02B Analyzing Past Trends And Economic Events (9:24)
04.03A Present Stock Market State (6:29)
04.04A Future Stock Market State (8:12)
04.04B Insights On Macroeconomic Factors (7:09)
05 01 Project Preview_1 (2:22)
05.02 Analyze Credit Scores (7:56)
05.03 Assess Loan Applicant Risk (7:35)
06 01 Project Preview_1 (1:12)
06.02A Pick Stocks With Company Evaluation (6:00)
06.03A Build A Trading Strategy (8:54)
06.03B Test Trading Hypthothesis (8:29)
07 01 Project Preview_1 (1:03)
07.02 Chatgpt And Sentiment Analysis (8:52)
07.03 Analyzing Sentiments On Social Media Posts- (8:45)
08 01 Project Preview_1 (1:03)
08.02A Fraud Detection With Chatgpt (7:37)
08.02B Detecting Exploitation Prone Weaknesses (8:01)
08.03A Red Flags And Anomaly Detection (6:07)
08.03B Anomaly Detection Techniques (8:01)
Conclusion (2:20)
Source Files
Data Science with Python and NumPy - Tensorflow
00. Course Intro (6:10)
01. Intro To Tensorflow (5:33)
02. Installing Tensorflow (3:52)
03. Intro To Linear Regression (9:26)
04. Linear Regression Model - Creating Dataset (5:49)
05. Linear Regression Model - Building The Model (7:22)
06. Linear Regression Model - Creating A Loss Function (5:57)
07. Linear Regression Model - Training The Model (12:43)
08. Linear Regression Model - Testing The Model (5:22)
09. Summary And Outro (2:55)
Intro to Tensorflow - Source Files
Data Science with Python and NumPy - Machine Learning Theory
00. Course Intro (6:05)
01. Quick Intro To Machine Learning (9:01)
02. Deep Dive Into Machine Learning (6:01)
03. Problems Solved With Machine Learning Part 1 (13:26)
04. Problems Solved With Machine Learning Part 2 (16:25)
05. Types Of Machine Learning (10:15)
06. How Machine Learning Works (11:40)
07. Common Machine Learning Structures (13:51)
08. Steps To Build A Machine Learning Program (16:34)
09. Summary And Outro (2:49)
Intro to Machine Learning Slides
Data Science with Python and NumPy - Numpy
00. Course Intro (5:11)
01. Intro To Numpy (6:21)
02. Installing Numpy (3:59)
03. Creating Numpy Arrays (16:55)
04. Creating Numpy Matrices (11:57)
05. Getting And Setting Numpy Elements (16:59)
06. Arithmetic Operations On Numpy Arrays (11:56)
07. Numpy Functions Part 1 (19:13)
08. Numpy Functions Part 2 (12:36)
09. Summary And Outro (3:01)
Source Files
Data Science with Python and NumPy - Review Sentiment Analysis
00. Course Intro (6:19)
01. How Machines Interpret Text (15:23)
02. Building the Model Part 1 - Examining Dataset (12:27)
03. Building the Model Part 2 - Formatting Dataset (15:14)
04. Building the Model Part 3 - Building the Model (10:30)
05. Building the Model Part 4 - Training the Model (5:42)
06. Building the Model Part 5 - Testing the Model.mp4 (9:26)
07. Course Summary and Outro (3:29)
Source Files
Learn to Graph Data with Python and Matplotlib
00. Course Intro (5:30)
01. Intro to Pyplot (5:11)
02. Installing Matplotlib (5:51)
03. Basic Line Plot (7:53)
04. Customizing Graphs (10:47)
05. Plotting Multiple Datasets (8:10)
06. Bar Chart (6:26)
07. Pie Chart (9:13)
08. Histogram (10:14)
09. 3D Plotting (6:28)
10. Course Outro (4:09)
Pyplot Code
Complete Beginners Data Analysis with Pandas and Python
00. Panda Course Introduction (5:43)
01. Intro To Pandas (7:55)
02. Installing Pandas (5:28)
03. Creating Pandas Series (20:34)
04. Date Ranges (11:29)
05. Getting Elements From Series (19:21)
06. Getting Properties Of Series (13:04)
07. Modifying Series (19:02)
08. Operations On Series (11:48)
09. Creating Pandas Dataframes (22:57)
10. Getting Elements From Dataframes (25:12)
11. Getting Properties From Dataframes (17:44)
12. Dataframe Modification (36:24)
13. Dataframe Operations (20:09)
14 Dataframe Comparisons And Iteration (15:35)
15. Reading Csvs (12:00)
16. Summary And Outro (4:14)
Source Files
(Prerequisite) Introduction to Machine Learning
00A What Is Machine Learning (5:26)
00B Types Of Machine Learning Models (12:17)
00C What Is Supervised Learning (11:04)
00D What Is Unsupervised Learning (8:17)
01 How Does A Machine Learning Agent Learn (7:38)
02 What Is Inductive Learning (4:11)
03 Performance Of A Machine Learning Algorithm (4:14)
04 Handle Noise In Data (5:22)
05 Powerful Tools With Machine Learning Libraries- (12:11)
Beginner Data Science and Machine Learning Bootcamp
01 Project Preview (3:29)
04-01 Create A Dataset (5:17)
04-02 Vectorize Text (16:27)
04-03 Build A Word Cloud (7:08)
04-04 Reduce Data Dimensionality With Principal Component Analysis (6:08)
04-05 Perform Unsupervised Classification With K-Means Clusters (17:33)
Source Files
Machine Learning Theory for Business
01-01 Hash Table Or Dictionary Visualized With Time And Space Complexity (4:19)
01-02 Types Of Machine Learning (12:09)
01-03 What Is Supervised Learning (9:59)
01-04 What Is Unsupervised Learning (7:43)
02 What Machine Learning Can And Cannot Do (11:27)
03a-01 What Is Linear Regression (4:37)
03a-02 What Is Logistic Regression (3:54)
03a-03 Make Decisions With Decision Trees (10:31)
03b-01 What Is Deep Learning (5:44)
03b-02 What Is A Neural Network (7:07)
04 What Are Machine Learning Libraries (11:59)
Machine Learning Fundamentals
00 Course Overview (13:46)
03-01 Probability And Information Theory Overview (5:15)
03-02 Combinatorics For Probability (8:44)
03-03 Law Of Large Numbers (10:38)
03-04 Calculate Center Of Distribution (7:40)
04-01 Uniform Distribution (5:25)
04-02 Gaussian Distribution (3:45)
04-03 Log-Normal Distribution (3:28)
04-04 Exponential Distribution (3:04)
04-05 Laplace Distribution (1:54)
04-06 Binomial Distribution (9:05)
04-07 Multinomial Distribution (3:59)
04-08 Poisson Distribution (4:21)
05 Calculate Error Of Machine Learning Model (8:44)
Source Files
Data Engineering and Machine Learning Masterclass
00-00 What Is Python (4:48)
00-01. Intro To Python (4:37)
00b-00 Course Overview (3:26)
03-01 Load And Clean A Public Dataset (8:55)
03-01B What Is One-Hot Encoding (10:02)
03-02 Build X And Y Data With One Hot Encoding (4:57)
03-03 Logistic Regression With One Hot Encoding (2:20)
04-04 Scale And Encode Data With Scikit-Learn (3:47)
04-04 What Is Scaling Data (6:36)
04-05 Build, Train And Test A Machine Learning Model (4:37)
05-01 Compare Decision Tree And Linear Regression Models (6:26)
05-01C What Is The Kbins Discretizer (4:54)
05-02 Bin Data With Kbins Discretizer (3:42)
05-03 Compare Binned Regression Models (3:39)
05-04 Build A Linear Regression Model On Stacked Data (3:20)
05-05A What Is K Means Clustering (11:58)
06-01 Build Univariate Nonlinear Transformatio (1:55)
06-01 What Is Gaussian Probability Distribution- (2:31)
06-01B What Is Poisson Distribution (1:08)
06-02 Build X Y Data With Poisson Distribution In Numpy (3:34)
06-02C What Is Logarithmic Data Transformation (2:34)
06-03 Build A Ridge Regression Model (3:41)
Source Files - Course Overview
Image Recognition Model
00. Course Intro (6:57)
01. Intro to Image Recognition (6:40)
02. Intro to MNIST (4:42)
03. Building a CNN Part 1 - Obtaining Data (15:40)
04. Building a CNN Part 2 - Building the Model (10:14)
05. Building a CNN Part 3 - Adding Loss and Optimizer Functions (4:57)
06. Building a CNN Part 4 - Train and Test Functions (10:58)
07. Building a CNN Part 5 - Train and Test the Model (9:17)
08. MNIST Image Recognition with Keras Sequential Model (13:24)
09. Summary and Outro (2:55)
Source Files
Build Machine Learning Models
01 What You-ll Learn-1 (8:47)
01-01 Course Overview (3:30)
01-02 Build Models On The Web (5:06)
02 What Is Supervised Learning-2 (14:41)
02-01 What Are Search Algorithms (7:21)
02-02 Depth First Search (9:00)
02-02b Build A Depth First Search Algorithm (8:26)
02-03 What Is Breadth First Search (bfs) (5:08)
02-03b Build A Breadth First Search Algorithm (6:56)
02-04 Depth Limited Search (3:58)
02-05 Iterative Deepening Depth First Search (5:32)
02-06 What Is Uniform Cost Search (6:04)
02-06b Build A Uniform Cost Search Algorithm (8:07)
02-07 Bidirectional Search (4:44)
03 Build Models On The Web-3 (5:06)
03-01 What Are Informed Search Algorithms (4:07)
03-02 What Is Greedy Best-first Search (8:16)
03-02b Build A Greedy Best First Search Algorithm (10:43)
03-03 What Is A Search (5:10)
04-01 How Does A Machine Learning Agent Learn (7:37)
04-02 What Is Inductive Learning (4:10)
04-03 Make Decisions With Decision Trees (10:50)
04-04 Performance Of A Machine Learning Algorithm (4:13)
04-05 Handle Noise In Data (5:20)
04-06 Statistical Learning (3:56)
05-01 What Is Logistic Regression (4:26)
05-03 Prepare Data For Logistic Regression (12:19)
05-03a How To Prepare Data (8:52)
05-04 Build A Logistic Regression Model (5:29)
05-04a How To Build A Logistic Regression Model (3:28)
05-04b What Is Optimization (12:10)
05-05 Optimize The Logistic Regression Model (12:44)
05-05a How To Optimize A Logistic Regression Model (12:45)
05-06 Train The Model (10:09)
05-07 Test The Model (2:33)
05-08 Visualize Results (5:38)
06.01 What Is Gradient Boosting-1 (1:54)
06.02 Prepare Data For Gradient Boosted Classification-2 (7:19)
06.03 Build Binary Classes-3 (6:12)
06.04a How To Shape Data For Classification-4 (2:58)
06.04b Shape Data For Classification-5 (7:06)
06.05a How To Build A Boosted Trees Classifier-6 (4:03)
06.05b Build A Boosted Trees Classifier-7 (4:37)
07.01 Build Input Functions-1 (3:55)
07.02 Build A Boosted Trees Regressor-2 (3:02)
07.03 Train And Evaluate The Model-3 (4:07)
Source Files
Build a Machine Learning Chatbot from Scratch
01-01 Build Patterns And Responses Training Data (6:34)
01-02 Tokenize Chat Data For Training (4:30)
02-01 Clean Chat Data For Machine Learning (3:04)
02-02 Build Bag Of Words For Ml Model (4:24)
02-03 Split Data For Machine Learning (3:34)
03-01 Build A Tensorflow Machine Learning Model For Chat (4:54)
03-02 Test Chatbot Machine Learning Model (9:09)
03-03 Categorize Chat Question With Ml (7:25)
03-04 Pick A Chatbot Response In Top Category (8:18)
Source Files
Build Advanced Chatbot with Transformer Neural Network
00-01 Introduction to Transformer Neural Networks (4:31)
00-02 Transformer Project Overview (7:59)
01-01 Connect To Google Drive Dataset In Colab (3:48)
01-02 Read Text Files In Python (9:17)
01-03 Read Movie Conversation Text File In Python (10:58)
01-04 Clean Text Data For NLP (6:09)
01-05 Remove Contractions From Text Data With Python (9:35)
01-06 Preprocess Text Data For Transformer Chatbot Ml (6:16)
02-01 Build Tokenizer With Tfds (7:31)
02-02 Add Padding To Tokenized Sentences With Python (3:06)
02-03 Build Tensorflow Dataset For ML (3:13)
03-01 Calculate Scaled Dot Product Attention (4:56)
03-02 Set Up Multi Head Attention Layer In Python Nn (5:22)
03-03 Split Attention Layer Into Multiple Heads (4:08)
03-04 Add Scaled Dot Product Attention And Final Layer (5:22)
04-01 Mask Padding Tokens With Python (4:38)
04-02 Build Lookahead Mask For Future Tokens (3:53)
05-01 Set Up Positional Encoding Layer In Neural Network (3:03)
05-02 Build Positional Encoding Layer With Tensorflow Keras (5:31)
06-01 Build Input Encoder For Neural Network (5:28)
06-02 Combine Input And Positional Encoding (5:36)
07-01 Set Up Decoder Layer With Python (6:31)
07-02 Combine Output And Positional Encoding For Decoder (5:28)
08-01 Combine encoding and decoding in NN (7:08)
08-02 Build custom ML model learning rate (3:37)
08-03 Build custom model loss function (3:17)
08-04 Compile neural network with Python (4:30)
08-04b Zero out padding tokens in attention (1:44)
08-05 Limit and pad tokenized sentences (5:30)
09-01 Handle new chatbot question input (5:13)
09-02 Decode tokens into words (2:30)
Source files
Python Chatbot Bootcamp with Pandas, NumPy and SciKit
01-01 Projects Preview (4:49)
01-01 What Is Natural Language Processing (5:39)
01-02 What Is Text Vectorization (7:34)
03-01 Train A Vectorizer (8:50)
03-02 Chat With The User (11:04)
04-01 Define A Basic Intent Classifier (7:42)
04-02 Define A Basic Generative Model (4:05)
04-03 Test The Chatbot (9:33)
Source Files
Text to Speech with Python Machine Learning, Deep Learning and Neural Networks
01-00 Course Overview - Text To Speech (1:13)
01-01 How Text To Speech Works (5:43)
01-02 What You-ll Need - Text To Speech (3:25)
03-01 Convert Text To Speech With Gtts (5:45)
04-00 What Are Pytorch, Tacotron 2 And Waveglow (4:29)
04-01 Load Models (3:50)
04-02 Convert Text To Speech With Pytorch (7:45)
05-00 What Is Pyttsx3 (1:20)
05-01 Load Available Voices (4:32)
05-02 Convert Text To Speech With Pyttsx3 (4:48)
Source Files
ChatGPT 4 for Marketing Professionals - 01 Introduction to ChatGPT 4 Prompts for Marketing
00 01 Introduction Of The Instructor (1:53)
01.01 Setting Up Your Chatgpt Account - A Step-By-Step Guide (6:04)
01.02 Tips For Getting The Best Responses From Chatgpt (9:55)
02 01 Building A Marketing Campaign Content Calendar With Chatgpt (10:34)
03 01 The Importance Of Identifying Your Target Audience_1 (3:08)
03.02 Using Chatgpt For Target Audience Research And Assessment (11:54)
01. Source Files
ChatGPT 4 for Marketing Professionals - 02 Build Social Media and Blog Posts
04 01 Project Preview (1:21)
04.02 Exploring Social Media Marketing And Automation (5:59)
04.03 Generating Social Media Posts (10:38)
04.04 Social Media Automation Tool - Socialbee - -Bonus- (6:40)
04.05 Automating Social Media Post Scheduling - -Bonus- (8:26)
04.06 Automating Social Media Reposting - -Bonus- (8:28)
04.07 Configuring Your Social Media Automation Timetable – -Bonus- (4:00)
05 01 Project Preview (1:11)
05.02 Generate Optimized Keywords And Blog Headlines (7:39)
05.03 Building An Seo-Enhanced Blog Post Quickly (10:07)
02. Source Files
ChatGPT 4 for Marketing Professionals - 03 Build Emails, Ads and Videos
06 01 Introduction To Email Marketing And Its Significance_1 (3:37)
06.02 Building Effective Email Sequences (7:27)
07 01 Crafting Sales Page Copy (8:05)
08 01 Project Preview (1:07)
08.02 Producing Facebook Ads (10:00)
08.03 Generating Google Ads (9:44)
08.04 Generate Ads For Instagram And Twitter (7:36)
09 01 Project Preview (1:09)
09.02 Generating Unlimited Video Concepts (10:33)
09.03 Crafting A Full Youtube Video Script (10:00)
09.04 Youtube Seo Strategies (8:54)
03 Source Files
ChatGPT 4 for Marketing Professionals - 04 Build Marketing Funnels and Analyze Customers
10 01 Project Preview (1:26)
10.02 Guides To Building Effective Marketing Funnels (4:01)
10.03 Defining Your Buyer Persona (9:38)
10.04 Generating A Lead Magnet (8:57)
10.05 Building Landing Page And Social Media Copy (9:02)
10.06 Composing A Comprehensive Email Sequence For Your Funnel (4:49)
11 01 Review Analysis And Optimization Of Products And Services (7:24)
04. Source Files
ChatGPT 4 for Marketing Professionals - 04 Build Marketing Funnels
12 01 Project Preview (1:57)
12.02 Homepage, About Us, And Contact Us Page Copy (10:14)
12.03 Generate Meta Title And Descriptions (4:58)
12.04 Website Development With Chatgpt Crash Course (25:32)
13 01 Project Preview (1:10)
13.02 Creating Product And Business Names (7:52)
13.03 Developing Professional Taglines And Slogans For Your Brand (7:32)
13.04 Writing Product Descriptions For Your Online Store (4:46)
13.05 Building Faq’S For Services Or Products (4:54)
14 01 Conclusion (2:08)
Bonus - Tips And Tricks (7:43)
05. Source Files
Advanced Business and Excel in ChatGPT
01 01 Course Requirement (2:31)
02 01 Project Preview (1:36)
02.02A Set Up Excel Spreadsheet With Gpt Add-In (8:37)
02.02B Excel With Chatgpt (4:51)
02.03 Write Excel Formulas With Chatgpt (9:39)
02.04 Use Chatgpt Formulas In Excel (16:18)
03 01 Project Preview (1:27)
03.02A Set Up Dashboard (7:51)
03.02B Set Up Data (7:11)
03.03A Use Chatgpt And Excel To Build An Investment Dashboard (11:37)
03.03B Generate More Formulas For Excel (11:34)
03.03C Placing Data On Dashboard (10:30)
04 01 Project Preview_1 (2:10)
04.02A Project Setup - Product Worksheet (11:59)
04.02B Setup Sales And Summary Sheet (9:22)
04.03A Build Advanced Chatgpt Excel Project (13:00)
04.03B Automating Product Name And Price Data (13:11)
04.03C Completing Sales Sheet Automation With Chatgpt (9:32)
04.03D Building Sales Overview Dashboard (8:37)
04.03E Refining The Pos System (11:14)
05 01 Project Preview_1 (2:18)
05.02 Meeting Agendas And Minutes (10:25)
05.03 Write A Business Proposal (11:18)
05.04 Build A Business Report (11:12)
05.05 Build A Business Plan (10:35)
05.06 Build A Business Performance Appraisal (10:39)
05.07 Build A Business Presentation (12:40)
05.08 Summarize Business Documents (11:44)
05.09 Write Job Descriptions (8:33)
05.10 Build White Papers (9:38)
05.11 Build Employee Handbooks (8:44)
05.12 Build Business Manuals (9:24)
06 01 Project Preview_1 (1:16)
06.02 Set Up Project (8:06)
06.03A Advanced Chatgpt 4 Business Project (10:10)
06.03B Chatgpt And Social Bee Side By Side (10:16)
06.03C Finishing Touches (12:26)
Source Files
ChatGPT & Auto-GPT Mastery and Advanced Applications
01. Short Demo - Introduction To The Course (2:25)
00 (Prerequisite) Introduction to HTML
01. Course Requirements (2:56)
02. What Is Jsbin (3:15)
03. Setting Up The Html Document (2:41)
04. Header Tags And Paragraphs Tags (4:06)
05. Styles (3:32)
06. Bold Underline And Italic Tags (3:10)
07. Adding In A Link (1:38)
08. Adding In A Image (3:01)
09. Adding A Link To An Image (1:55)
10. Lists (4:03)
11. Tables (3:29)
12. Different Kinds Of Input (4:59)
13. Adding In A Submit Button (3:01)
14. Scripts And Style Tags (3:27)
01 (Prerequisite) Introduction to CSS
01. Course Requirements (3:41)
02. Html Styles Crash Course (4:45)
03. Adding Code To The CSS (4:46)
04. Adding In IDs To The CSS (5:16)
05. Classes In CSS (2:39)
06. Font Families (5:04)
07. Colors In CSS (5:44)
08. Padding In CSS (3:06)
09. Text Align And Transforms (3:14)
10. Margins And Width (5:33)
11. Changing The Body (4:11)
12. Latin Text Generator (1:57)
13. Adding In A Horizontal Menu With HTML And CSS (7:53)
14. Adding A Background Image (4:04)
15. Playing Around With Margins In CSS (2:20)
02 (Prerequisite) Introduction to JavaScript
01. Variables (5:36)
02. Javascript (10:24)
03. Numbers (4:52)
04. Booleans (5:22)
05. If Statements (4:27)
06. Arrays (8:31)
07. For Loops (9:16)
08. While Loops (4:34)
09. Objects (8:02)
10. Functions (6:09)
11. Foreach (3:54)
12. Map Functions (5:22)
13. Using Objects As Dictionary (2:45)
14. Switch Statements (6:38)
15. Destructuring (5:30)
16. Spread Operator (6:56)
17. String Templates (6:37)
18. Error Handling (5:45)
19. Let And Const Keywords (3:39)
20. Do-While (1:45)
21. Sets (5:42)
22. Maps (4:39)
23. Stacks (6:06)
24. Queues (11:49)
25. For Loop (5:11)
26. Recursive Functions (7:13)
27. Loop Labeling (5:18)
28. 2D Arrays (21:59)
29. Settimeout (7:02)
30. Sentimental (11:21)
31. Functions With Optional Parameters (15:10)
32. Basic Regular Expression (5:53)
33. Handle Keypress Events (22:45)
34. Priority Queue (15:54)
35. Add-delete Object Property (2:45)
36. Example With Sets Part 1 (28:49)
36. Example With Sets Part 2 (43:20)
37. Concat (3:12)
38. Flat And Flatmap (2:06)
03 (Prerequisite) Command Line Fundamentals
01-01 Why All Developers Need To Know The Command Line (8:50)
01-02 What Are Linux And Unix Terminals (8:04)
02-01 What You-ll Need (1:20)
02-02 Install Linux Command Line On Windows (3:18)
03-01 Build Your First Command In The Command Line (3:48)
03-02 Navigate Directories In The Command Line (6:33)
03-03 Build And Edit A New File In The Command Line (7:27)
03-04 Move Files In The Command Line (9:00)
Source Files
04 (Prerequisite) Install Node and npm
00 What Is Node JS (8:22)
01 What Is Yarn (2:16)
02 How to Install Node and NPM on Windows-R (8:41)
02 Install Yarn On Mac (4:22)
Source files
05 (Prerequisite) Introduction to React
00 Why You Should Learn React (5:30)
01 React Introduction (12:33)
02 Set up a Container (8:13)
03 Generate a List (6:46)
04 Add Items to the List (6:34)
05 Clear Input Field (10:26)
06 Remove a Task (10:39)
Source Files
ChatGPT 4 for Web Developers - Build an E-commerce Site with JavaScript
02. Project Setup (16:38)
03. Css With Chatgpt Part 1 (27:38)
04. Css With Chatgpt - Part Two (20:52)
Source Files
Build eCommerce Website with ChatGPT and React JS
05. Styling The Product-Info Page (24:47)
06. Links, Burger Menu And Filters (16:16)
02 Source Files
Build Website Shopping Cart with ChatGPT and React JS
07. Implementing The Shopping Cart - Part One (16:54)
08. Implementing The Shopping Cart Part Two (10:30)
09. Total Price And Shipping Calculations (24:13)
10. Checkout Page (18:43)
03 Source Files
Web Development with ChatGPT and React JS
11. Styling The Site Pt1 (15:51)
12. Styling The Site Pt2 (17:25)
13. Legacy Pages (23:06)
04 Source Files
Build Login Page with ChatGPT and React JS
14. Login Register Dashboard (25:55)
15. Local Storage For User Info (20:34)
05 Source Files
Google Cloud Professional Machine Learning Engineer Certification Introduction
00-Course Preview (4:02)
01 Why Use The Cloud For Machine Learning (2:38)
02 Benefits Of Cloud Computing- (1:23)
03 Public Vs Private Cloud Computing (3:18)
04 Managed Vs Unmanaged Cloud Computing (1:30)
05 Iaas Vs Paas Vs Saas In Cloud Computing (3:33)
06 Google Cloud Vs Aws Vs Azure For Machine Learning (3:32)
07 Build A Google Cloud Project For Machine Learning (6:45)
08 What Is A Service Account In Google Cloud Platform (1:59)
09 Build A Service Account And Key In Google Cloud (6:52)
10 Image Dataset For Machine Learning From Cloud Storage (2:12)
12 Build An Image Dataset For Classification From A Cloud Storage Bucket (5:36)
13 Train An AutoML Image Classifier Machine Learning Model (6:27)
14 Deploy Machine Learning Model To Cloud Endpoint (3:38)
15 Make A Prediction With A Cloud Machine Learning Model (5:14)
16 Sign In To Google Cloud (2:46)
17 Build A Bigquery Dataset In Google Cloud Console (8:24)
18 Build A Cloud Storage Bucket In Google Cloud (8:15)
19 What Is Dataflow API In Google Cloud (2:44)
20 What Is Pubsub In Google Cloud (4:24)
21 Build Data Streaming Dataflow Pipeline With Google Cloud Api (9:39)
22 Analyze Streaming Data With Bigquery Google Standard Sql (6:39)
23 Visualize Bigquery Cloud Data With Google Data Studio (3:54)
Source Files
Microsoft Certified Azure Data Scientist Associate Preparation
00A Course Overview (3:09)
00A-01 What Is Microsoft Azure Machine Learning (3:24)
00A-02 What Is Microsoft Certified Azure Data Scientist Associate (5:10)
02-01 Why Use The Cloud For Machine Learning (2:38)
02-03 Public Vs Private Cloud Computing (3:18)
02-04 Managed Vs Unmanaged Cloud Computing (1:30)
02-05 Iaas Vs Paas Vs Saas In Cloud Computing (3:33)
02-06 Google Cloud Vs Aws Vs Azure For Machine Learning (3:32)
03 What Is Azure Machine Learning Studio (2:17)
04-01 Build An Azure Machine Learning Workspace (12:51)
04-02 Build A New Compute Cluster In Microsoft Azure Ml (6:08)
04-03 Build A Pipeline In Microsoft Azure Ml Designer (4:25)
04-03A What Is Azure Machine Learning Designer (3:16)
05-01 Build A Dataset In Microsoft Azure Ml Designer (3:48)
05-02 Clean Missing Data In Microsoft Azure Ml Designer (10:26)
05-03 Normalize Data In Microsoft Azure Ml Studio (4:24)
05-04 Run A Data Transformation Pipeline In Microsoft Azure Ml Designer (2:09)
06-00 What Is Linear Regression (5:03)
06-01 Build A Model Training Pipeline In Microsoft Azure Ml Studio (5:03)
06-02 Evaluate A Machine Learning Model In Microsoft Azure Ml (7:08)
Source Files
Beginners Machine Learning Masterclass with Tensorflow JS
00-01b What You-ll Learn (7:12)
00-02 What Is Tensorflow Js (4:28)
00-03 Load Tensorflow Object (4:28)
01 What Is Machine Learning (6:39)
01b-01 Build A Scatter Plot (8:41)
01b-02 Build A Bar Chart (5:33)
01b-03 Build A Histogram (6:39)
01c-01 Build Sample Data (5:16)
01c-02 Build The Model (11:14)
01c-03 Make A Prediction (7:47)
01d-01 Generate Data (13:38)
01d-02 Visualize Data (16:10)
02-00 What Is Linear Regression (7:52)
02-01 Prepare Training Data (7:10)
02-02 Build The Model (14:05)
02-03 Make A Prediction (3:53)
02b-01 Set Up The Canvas (3:48)
02b-02 Draw A Data Sample (6:20)
02b-03 Create Loss And Prediction Functions (6:00)
02b-04 Collect User Input For Data (8:50)
02b-05 Visualize Linear Regression With Dynamic Data (6:46)
03-01 Set Up The Canvas (11:00)
03-02 Visualize Linear Regression With Dynamic Data (16:33)
04-01 Generate Samples (6:21)
04-02 Generate A Prediction Equation With Weights (6:54)
04-03 Train The Model (5:26)
04-04 Visualize Predictions (18:01)
04-05 Visualize Prediction Error (10:00)
05-01 Load Models Into Html (5:51)
05-02 Train Model On Images (13:13)
05-03 Make A Prediction (6:58)
Source Files
Beginners Guide to Neural Networks in Tensorflow JS
00 What You-ll Learn (7:44)
04-00a What Is Deep Learning (6:08)
04-00b What Is A Neural Network (8:06)
04-01 Build A Perceptron (13:26)
04-02 Build A Sigmoid Function (8:01)
04-03 Build A Sigmoid Perceptron (7:35)
04-04 Build A Relu Activation Function (7:12)
04-05 Build A Leaky Relu Activation Function (6:10)
05-01 Build Neural Network Layers (9:57)
05-02 Train And Test The Neural Network (11:24)
06-01 Build A Dataset-1 (8:26)
06-02 Build A Neural Network-2 (5:35)
06-03 Train The Neural Network-3 (10:05)
06-04 Make A Prediction With The Neural Network-4 (8:43)
07-00 What Is Cross Validation-1 (8:24)
07-01 Load A Model Into Html-2 (4:57)
07-02 Use A Neural Network In Your Website-3 (8:49)
07-03 Show Neural Network Results On Website-4 (5:34)
08-01 Build A Dataset For Xor (6:32)
08-02 Build A Neural Network For Xor (5:19)
08-03 Train And Test The Neural Network (11:06)
09-01 Load An Rnn Into Your Website (5:37)
09-02 Set Up The Canvas (7:06)
09-03 Draw With A Neural Network (8:50)
10-01 Load An Image For Object Detection (6:13)
10-02 Load A Neural Network For Object Detection (6:15)
10-03 Outline Objects In The Image (12:17)
11-01 Build A Deep Neural Network With Gradient Descent From Scratch-1 (9:21)
11-03 Build A Deep Neural Network With Gradient Descent With Tensorflow Js-2 (11:24)
11-04 Build A Deep Neural Network With Backpropagation-3 (7:03)
11-05 Build The Backpropagation-4 (16:56)
12-01 Reduce Neural Network Error-1 (17:12)
12-02 Build A Gradient Descent Algorithm-2 (8:48)
13 Train The Deep Neural Network With Gradient Descent (15:24)
Tensorflow JS Source Files
Advanced Machine Learning with TensorFlow.js
02-01 Load The Model With Text (4:18)
02-02 View Model Results Of Text Toxicity (6:40)
02-03 Clean Up Prediction Results (6:18)
03-01 Set Up The Speed Recognition Model (6:00)
03-02 Set Up The Canvas (3:26)
03-03 Classify Words Through Microphone (6:55)
03-04 Draw From User Commands (7:35)
03-05 Optimize The Drawing (5:53)
04-01 Tidy Tensors (6:26)
04-02 Keep Tensors (3:10)
04-03 Dispose Tensors (2:41)
04-04 Build A Memory Leak Example (4:35)
05-01 Load Json Data (7:34)
05-02 Convert Json Data To Tensor (9:08)
05-03 Visualize Dataset With Tf-Vis (5:38)
05-04 Build And Train Model (10:22)
05-05 Visualize Model-s Training Epochs (9:12)
05-06 Make A Prediction (13:49)
05-07 Visualize Prediction (9:09)
06-01 Load Dataset From Json File (6:48)
06-02 Visualize Dataset-s Features (9:26)
06-03 Build A Multi Layer Model (7:43)
06-04 Extract Inputs And Outputs (7:10)
06-05 Normalize Data (4:47)
06-06 Train The Model (6:01)
06-07 Evaluate Model Performance (6:12)
07-00 What Is Logistic Regression (4:32)
07-00B Calculate Logistic Regression Accuracy (5:20)
07-01 Build A Logistic Regression Model (7:08)
07-02 Train The Logistic Regression Model (15:20)
07-03 Visualize Logistic Regression Results (12:52)
07-04 Visualize Original Data (12:13)
07-05 Visualize Model Error (7:37)
08-00 What Is Fast Fourier Transform (2:42)
08-01 Build And Visualize A Dataset (10:48)
08-02 Visualize Frequencies With Fast Fourier Transform (11:53)
08-03 Visualize Inverse Fast Fourier Transform (5:44)
09-00 What Is Principal Component Analysis (6:13)
09-01 Build Principal Component Analysis (6:24)
09-02 Calculate Variance Of Data And Principal Component Analysis (9:28)
09-03 Visualize Data Slices (12:01)
09-04 Visualize Principal Component Analysis Results (3:03)
Source Files
Advanced Neural Networks with TensorFlow.js-Export Only
00B What Is A Neural Network (8:08)
00A What Is Deep Learning (6:10)
02-00 What Is One Hot Encoding (6:53)
02-01 Build Training Data (7:34)
02-02 Build The Neural Network (6:48)
02-03 Train The Neural Network (9:33)
02-04 Make A Prediction (10:11)
03-01 Build Training Data To Represent Images (12:15)
03-02 Build The Convolutional Neural Network (10:39)
03-03 Train The Convolutional Neural Network (9:06)
03-04 Make A Prediction Of Number Of Lines (15:05)
04-00 What Is A Recurrent Neural Network (6:38)
04-01 Generate Sequence And Label (6:25)
04-02 Generate Dataset (6:02)
04-03 Build The Lstm Model (4:55)
04-04 Train The Model (11:25)
06-01 Process Iris Data (7:37)
06-02 Convert Data To Tensors (8:45)
06-03 Separate Training And Testing Data (8:54)
06-04 Create Training And Testing Datasets (4:42)
06-05 Build The Model (9:29)
06-06 Train The Model (4:11)
06-07 Make A Prediction (8:45)
07-01 Load Model And Dataset (5:57)
07-02 Get User Input For Sentiment Analysis (10:59)
07-03 Make A Prediction (7:11)
08-00 What Is A Convolutional Neural Network (19:29)
08-01 Set Up Canvas To Load Image Data (10:36)
08-02 Load Mnist Dataset (6:47)
08-03 Separate Training And Testing Data (5:40)
08-04 Build The Model (6:48)
08-04A What Are The Network-s Layers (14:14)
08-05 Train The Model (11:27)
08-06 Create Training Batches (6:14)
08-07 Create Testing Batches (11:31)
08-08 Fit Neural Network Through Data (8:54)
Source Files
(Prerequisite) Introduction to Android Studio
01. Downloading And Installing Android Studio (6:53)
00. Introduction (3:27)
02. Exploring Android Studio Interface (12:59)
03. Understanding File Hierarchy (12:19)
04. Exploring Activity-Layout Relationship (19:36)
05. Setting Up An Emulator (7:01)
06. Running App And Implementing User Interaction (6:45)
07. Debugging An App (6:11)
08. Summary And Outro (4:07)
Source Files
(Prerequisite) Introduction to Kotlin
01. Introduction To Variables (7:04)
00. Introduction (6:12)
02. Basic Operations (9:18)
03. Nullable Variables (5:24)
04. Collections Intro (7:27)
05. Mutable Lists And Arrays (6:53)
06. If Statements And Expressions (8:11)
07. When Statements And Expressions (3:30)
08. While Loops (6:46)
09. For In Loops (4:55)
10. Introduction To Functions (7:55)
11. Functions With Parameters And Return Values (7:29)
12. Classes And Objects Introductions (16:37)
13. Subclassing And Superclassing (13:12)
14. Summary And Outro (4:41)
Source FIles
Python and Android Tensor Flow Lite - Machine Learning for App Development
00-01 What You-ll Need (4:29)
00-00 Course Overview (3:12)
04b Project Preview (2:17)
05-01 Build A Linear Regression Model With Python (15:06)
05-02 Convert Python Model To Tensorflow Lite (5:38)
06-03 Build A New Android Studio App (7:39)
06-04 Build App Layout (10:18)
07-05 Load Machine Learning Model (4:53)
07-06 Use Machine Learning Model (5:18)
07-07 Connect App Layout To Model (6:08)
08-00 Project Preview (1:49)
08-00 What Is Logistic Regression (4:32)
09-01 Load And Process Data For Logistic Regression With Scikit Learn (9:14)
09-02 Build A Logistic Regression Model With Python (8:01)
09-03 Convert Logistic Regression Model To Tensorflow Lite (2:38)
10-04 Build A New Android Studio App With Tf Lite Model (5:48)
10-05 Build App Layout For Logistic Regression (9:26)
11-06 Load Logistic Regression Model In Android Studio (5:01)
11-07 Use Logistic Regression Model In Android (8:46)
11-08 Enable App User Interaction With Machine Learning Model (9:54)
Source files
CoreML SwiftUI Masterclass - Machine Learning App Development
00-01 What You-ll Need (5:56)
00-00 Course Overview (6:54)
00-02 What Is Coreml (6:43)
01-00A What Is Sentiment Analysis (4:39)
01-00B Natural Language Framework (4:32)
01-01 Build A New Swiftui App For Sentiment Analysis (8:59)
01-02 Perform Sentiment Analysis In SwiftUI (7:38)
01-03 Change Color Depending On Sentiment (4:56)
02-01 Train A Model With CreateML (12:13)
02-02 Test The Model With CoreML In An App (14:17)
02-03 Display Prediction Accuracy (6:41)
03-01 What Is Deep Learning (6:10)
03-02 What Is A Neural Network (8:08)
04-01 Load A CoreML Model Into A New Xcode Project (11:00)
04-02 Add Images For Classification (6:31)
04-03 Enable User To Loop Through Image (5:40)
04-04 Import CoreML Model Into The View (5:28)
04-05 Resize Image For Model (6:26)
04-05A Resizing Image Overview (7:44)
04-06 Convert Image To Buffer For Model (8:55)
04-06A Image To Buffer Overview (6:55)
04-07 Test The Model On Image Classification (14:31)
05-00 Tip - How To Unhide Library Folder (1:22)
05-01 Build A New Xcode Project To Compile Model (4:44)
05-02 Build A Playground With Object Detection Model (4:28)
05-03 Instantiate A Model 05-Object (6:12)
05-04 Build An Image Analysis Request (7:23)
05-05 Resize Image For Model (9:36)
05-06 Convert Image To Buffer For Model (9:47)
05-07 Test Object Detection On Image (4:53)
Source Files
Beginners R Programming: Data Science and Machine Learning
1st Hour - Intro To R (51:17)
2nd Hour- Control Flow And Core Concepts (64:28)
3rd Hour Matrices, Dataframes, Lists And Data Manipulationb (77:00)
4th Hour - Ggplot And Intro To Machine Learning (68:55)
5th Hour - Conclusion (47:25)
Source Code
R Programming: Practical Data Science and Modeling
2) 2nd Hour - Functions In R (54:57)
1) 1st Hour - Course Overview And Data Setup (57:35)
3) 3rd Hour - Regression Model (63:39)
4) 4th Hour - Regression Models Continued And Classification Models (57:04)
5) 5th Hour - Classification Models Continued, Rmark Down And Excel (78:31)
Source Files
16-04 Test Post Request From Python Web App To Chatgpt
Lesson content will be unlocked within 30 minutes.
Teachable is working on this bug.
No further action will be required on your part
.
Thank you for your patience