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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
02 14 Summarize A Company’S Earnings Report Calls
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