English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 121 lectures (13h 05m) | 9.47 GB
Recorded with GPT-4! ChatGPT API, Whisper, Embeddings, DALL-E, and Tons of Projects!
Unleash the Power of AI: Master OpenAI’s APIs, including GPT-4, DALL-E, and Whisper in this Comprehensive and Hands-On Course. This is a brand new course, recorded with GPT-4!
Step into the world of artificial intelligence and discover how to harness OpenAI’s cutting-edge APIs, including GPT3, GPT-3.5, GPT4, DALL-E, and Whisper, to create groundbreaking applications and solutions. This immersive, project-driven course is designed for learners of all backgrounds and skill levels, providing a solid foundation in AI-driven development.
In this comprehensive course, you will:
- Develop a deep understanding of OpenAI’s generative models and their potential applications
- Master GPT-4 for natural language processing, including text generation, summarization, translation, and more
- Use GPT-4 to debug code, improve code, and even write code from scratch
- Generate visually stunning images and artwork using DALL-E based on textual prompts
- Convert spoken audio into accurate transcriptions and translations with the power of Whisper
- Use AI Embeddings to distill, index, search, and compare text, unveiling the geometric power for comparing words, paragraphs, and documents
Real-World Projects for Practical Experience:
- Create a dynamic Q&A Bot using GPT-4
- Create a visual color palette search engine with GPT-4
- Write an interactive code reviewing assistant with GPT-4
- Create an AI-powered Spotify playlist generator
- Analyze the sentiment of Reddit comments using GPT-4
- Summarize books of any size into a couple of paragraphs
- Create your own interactive, infinite Choose Your Own Adventure application with DALL-E and GPT-4
- Generate an Emedding-Powered movie recommendation algorithm
Throughout the course, you will engage in hands-on projects and real-world examples, allowing you to immediately apply your newly-acquired knowledge and skills. We also delve into:
- Best practices for prompt engineering, tokenization, and temperature settings
- Strategies for optimizing API performance, error handling, and resource management
- The ethical considerations and challenges associated with AI-driven development
Whether you’re a software developer, data scientist, or an AI enthusiast, this course will equip you with the expertise to integrate OpenAI’s APIs into your projects and create innovative AI-powered solutions.
Embark on your AI journey and transform your skills with this comprehensive and engaging course. Enroll today and start unlocking the limitless potential of OpenAI’s GPT-4, DALL-E, and Whisper APIs!
What you’ll learn
- Master OpenAI’s GPT-4 and its text completion capabilities
- Understand GPT parameters to fine-tune the model’s performance
- Write, analyze, and debug code in any language using GPT-4
- Structure and refine GPT’s output for consistency and clarity
- Customize GPT-4 to address specific use cases and unique requirements
- Generate and edit images using DALL-E 2
- Employ text embeddings for searching, classifying, and understanding text
- Build an embedding-powered recommendation algorithm
- Use Whisper to translate and transcribe audio files
Table of Contents
Introduction
1 Welcome Course Overview
2 Getting Access To Our Discord Community
3 A Brief History of OpenAI
4 Lets Talk About GPT
5 OPTIONAL The Transformer Architecture
6 Signing Up For An Account
7 Getting The Course Code
8 Getting The Course Slides
Getting Started
9 Install Requirements
10 The Great OpenAI 1x Upgrade Important
11 Our First Completion Request
12 For Windows Users Editing Text Files
13 Hiding Our API Key
14 Understanding Tokens
15 maxtokens
16 Stop Sequences
17 N and Echo
18 The Different Completion Models
19 Comparing Model Performance and Pricing
Prompt Engineering
20 The Elements of a Good Prompt
21 Controlling The Output Format
22 Summarization Prompts
23 Data Extraction Prompts
24 Sentiment Analysis Prompts
25 ZeroShot Vs FewShot Prompting
26 Lets Think Step By Step Prompting
27 Text Transformation Prompts
Color Palette Generator Project
28 Introducing The Color Palette Project
29 Color Rendering in Colaboratory
30 Writing The Color Palette Generator Prompt
31 Writing a ColorSwatch Rendering Function
32 Setting Up The Flask Server
33 Integrating OpenAI With Server
34 Writing the Palette Endpoint
35 Creating The Form
36 Rending The Colors In The Browser
37 Copy and Paste Functionality
38 Styling The Color Blocks
39 Styling The Form
40 Refactoring Our FrontEnd Code
Important API Parameters
41 Temperature
42 Understanding Top P
43 Frequency Penalty
44 Presence Penalty
45 Streaming Responses
The Chat API GPT4
46 Introducing The Chat API
47 Our First Chat Request
48 Important Note On Pricing
49 Prompting With Properly Formatted Messages
50 Note on GPT35Turbo Versions
51 Rewriting a Completion Prompt In Chat Format
52 Chat API Parameters
Building A GPT4 Chatbot
53 Introducing Our Chatbot Project
54 Writing The Basic Chatbot Structure
55 Persisting Messages Across Requests
56 Adding Optional Personalities
57 Colorizing The Chatbot Output
Working With GPT4 And Code
58 Asking GPT4 To Explain Code
59 Calculating Time Complexity With GPT4
60 Translating JS To Python With GPT4
61 Fixing Code Bugs With GPT4
62 Generating Code From Scratch With GPT4
Cost Estimation With TikToken
63 Counting Tokens With TikToken
64 Counting GPT4 Message Tokens
GPT4 Automatic Code Reviewer
65 Introducing The Basic Code Reviewer
66 Building The Basic Code Reviewer Pt 1
67 Building The Basic Code Reviewer Pt 2
68 Introducing The Interactive Code Reviewer
69 Interactive Code Reviewer Prompt
70 Interactive Code Reviewer Walkthrough
GPT4 AI Spotify Playlist Generator Project
71 Introducing The Spotify Project
72 Writing The Playlist Generating Prompt
73 Finishing The Playlist Prompt
74 Getting Spotify Developer Credentials
75 Spotify Authentication Via Python
76 Searching For Spotify Tracks Via Python
77 Creating Spotify Playlists Programmatically
78 Adding in OpenAI
79 Accepting Command Line Arguments
80 Overview of the Polished Solution
Embeddings
81 Requirements
82 Introducing Embeddings
83 Generating a Single Embedding
84 Introducing The Movie Embedding Visualization
85 Getting our Movie Data
86 Getting Our Movie Data Ready
87 Add your Tenacity Import
88 Generating Embeddings for 5000 Movies
89 Visualizing Our Embeddings With Atlas
90 Recommending Movies Using Our Embeddings
Using Embeddings To Enhance GPT4
91 Expanding GPT4 Knowledge With Embeddings
92 Gathering Our Embeddings
93 Implementing QA With Embeddings GPT4
Sentiment Analysis Project
94 Introducing The Reddit Sentiment Analysis Project
95 Collecting Comments From Reddit
96 Analyzing Sentiment In The Comments
97 Plotting The Results
Book Summarizer Project
98 Introducing The Book Summarizer
99 Preparing Book Text For Summarization
100 Context Window Math
101 Summarization Logic
102 Caching Results
103 Performing a MetaSummary With GPT4
The DALLE API
104 Intro To DALLE
105 Making a DALLE Request
106 Saving DALLE Images
107 Alternative Approach To Saving Images
108 Requesting Image Variations
109 DALLE Image Edits
Stable Diffusion Choose Your Own Adventure App
110 Introducing StabilityAI and Stable Diffusion
111 Using the Stability SDK
112 Introducing The Choose Your Own Adventure Project
113 GPT4 CYOA Text Generation
114 Stable Diffusion CYOA Image Generation
Whisper Audio To Text
115 Introducing Whisper
116 The Basics of Whisper
117 Installing PyAudio
118 Providing a Prompt to Whisper
119 Translating Audio With Whisper
120 Transcribing NonEnglish Audio
121 Running The Whisper Model Locally
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