GPT-4 for Developers, Campesato O., 2024

GPT-4 for Developers, Campesato O., 2024.
    
   This book contains basic code samples that are written in Python, and their primary purpose is to familiarize you with basic Python to help you understand the Python code generated via ChatGPT. Moreover, clarity has higher priority than writing more compact code that is more difficult to understand (and possibly more prone to bugs). If you decide to use any of the code in this book, you ought to subject that code to the same rigorous analysis as the other parts of your code base.




DeepMind and Games.
DeepMind is the force behind the AI systems AlphaStar and AlphaGo, which defeated the best human players in Go (which is considerably more difficult than chess). These games provide “perfect information,’’ whereas games with “imperfect information” (such as poker) have posed challenges for machine learning (ML) models.

AlphaGo Zero (the successor of AlphaGo) mastered the game through self-play in less time and with less computing power. AlphaGo Zero exhibited extraordinary performance by defeating AlphaGo 100-0. Another powerful system is AlphaZero, which also used a self-play technique to play Go, chess, and shogi, achieving SOTA performance results.

Contents.
Chapter 1: ChatGPT and GPT-4.
What is Generative AI?.
Key Features of Generative AI.
Popular Techniques in Generative AI.
What Makes Generative AI Different.
Conversational AI Versus Generative AI.
Primary Objectives.
Applications.
Technologies Used.
Training and Interaction.
Evaluation.
Data Requirements.
Is DALL-E Part of Generative AI?.
Are ChatGPT-3 and GPT-4 Part of Generative AI?.
DeepMind.
DeepMind and Games.
Player of Games (PoG).
OpenAI.
Cohere.
Hugging Face.
Hugging Face Libraries.
Hugging Face Model Hub.
AI21.
InflectionAI.
Anthropic.
What is Prompt Engineering?.
Prompts and Completions.
Types of Prompts.
Instruction Prompts.
Reverse Prompts.
System Prompts Versus Agent Prompts.
Prompt Templates.
Prompts for Different LLMs.
Poorly Worded Prompts.
What is ChatGPT?.
ChatGPT: GPT-3 “on Steroids?”.
ChatGPT: Google “Code Red”.
ChatGPT Versus Google Search.
ChatGPT Custom Instructions.
ChatGPT on Mobile Devices and Browsers.
ChatGPT and Prompts.
GPTBot.
ChatGPT Playground.
ChatGPT and Medical Diagnosis.
Plugins, Advanced Data Analysis, and Code Whisperer.
Plugins.
Advanced Data Analysis.
Advanced Data Analysis Versus Claude 2.
Code Whisperer.
Detecting Generated Text.
Concerns About ChatGPT.
Code Generation and Dangerous Topics.
ChatGPT Strengths and Weaknesses.
Sample Queries and Responses from ChatGPT.
Alternatives to ChatGPT.
Google Bard.
YouChat.
Pi from Inflection.
Machine Learning and ChatGPT: Advanced Data Analysis.
What is InstructGPT?.
VizGPT and Data Visualization.
What is GPT-4?.
GPT-4 and Test-Taking Scores.
GPT-4 Parameters.
GPT-4 Fine-Tuning.
ChatGPT and GPT-4 Competitors.
Bard.
CoPilot (OpenAI/Microsoft).
Codex (OpenAI).
Apple CPT.
PaLM-2.
Med-PaLM M.
Claude 2.
LlaMa-2.
How to Download LlaMa-2.
LlaMa-2 Architecture Features.
Fine-Tuning LlaMa-2.
When is GPT-5 Available?.
Summary.
Chapter 2: ChatGPT and Python.
Simple Calculator.
Simple File Handling.
Simple Web Scraping.
Basic Chatbot.
Basic Data Visualization.
Basic Pandas.
Generate Random Data.
Recursion: Fibonacci Numbers.
Object Oriented Programming.
Asynchronous Programming with asyncio.
Working with Requests in Python.
Image Processing with PIL.
Exception Handling.
Generators in Python.
Roll 7 or 11 with Two Dice.
Roll 7 or 11 with Three Dice.
Roll 7 or 11 with Four Dice.
Mean and Standard Deviation.
Summary.
Chapter 3: ChatGPT and Data Visualization.
Working with Charts and Graphs.
Bar Charts.
Pie Charts.
Line Graphs.
Heat Maps.
Histograms.
Box Plots.
Pareto Charts.
Radar Charts.
Treemaps.
Waterfall Charts.
Line Plots with Matplotlib.
A Pie Chart Using Matplotlib.
Box-and-Whisker Plots using Matplotlib.
Time Series Visualization with Matplotlib.
Stacked Bar Charts with Matplotlib.
Donut Charts Using Matplotlib.
3D Surface Plots with Matplotlib.
Radial or Spider Charts with Matplotlib.
Matplotlib’s Contour Plots.
Stream Plots for Vector Fields.
Quiver Plots for Vector Fields.
Polar Plots.
Bar Charts with Seaborn.
Scatter Plots with Regression Lines Using Seaborn.
Heatmaps for a Correlation Matrix with Seaborn.
Histograms with Seaborn.
Violin Plots with Seaborn.
Pair Plots Using Seaborn.
Facet Grids with Seaborn.
Hierarchical Clustering.
Swarm Plots.
Joint Plots for Bivariate Data.
Point Plots for Factorized Views.
Seaborn's KDE Plots for Density Estimations.
Seaborn's Ridge Plots.
Summaiy.
Chapter 4: Linear Regression With GPT-4.
What is Linear Regression?.
Examples of Linear Regression.
Metrics for Linear Regression.
Coefficient of Determination (R-).
Linear Regression with Random Data with GPT-4.
Linear Regression with a Dataset with GPT-4.
Describe the Features of the death.csv Dataset.
The Preparation Process of the Dataset.
The Exploratory Analysis.
Detailed EDA on the death.csv Dataset.
Bivariate and Multivariate Analyses.
The Model Selection Process.
Code for Linear Regression with the death.csv Dataset.
Describe the Model Diagnostics.
Additional Model Diagnostics.
More Recommendations from GPT-4.
Summaiy.
Chapter 5: Visualization with Generative AI.
Generative AI and Art and Copyrights.
Generative AI and GANs.
GANs (Generative Adversarial Networks).
What is Diffusion?.
Diffusion Image Sample.
Diffusion Models Versus GANs.
What are Diffusers and DDPMs?.
CLIP (OpenAI).
GLIDE (OpenAI).
Text-to-Image Generation.
Stability Al/Stable Diffusion.
Imagen (Google).
Make-a-Scene (Meta).
Diffuse the Rest.
GauGAN2 (NVIDIA).
PromptBase.
Limitations of Text-to-Image Models.
Text-to-Image Models.
The DALL-E Models.
DALL-E.
DALL-E 3.
Paid Accounts for DALL-E.
Invoking the DALL-E API.
DALL-E 2.
DALL-E 2 Overview.
The DALL-E 2 Model.
DALL-E 2 Content Preparation.
DALL-E-Bot.
DALL-E Demos.
Text-to-Video Generation.
Meta (Make-a-Video).
Imagen Text-to-Video.
Ruben Villegas and Google (Phenaki).
Text-to-Speech Generation.
Whisper (OpenAI).
Summary.
Index.



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