Python 3 and Machine Learning Using ChatGPT / GPT-4 (MLI Generative AI Series)

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LICENSE, DISCLAIMER OF LIABILITY, AND LIMITED WARRANTY
Title Page
Copyright Page
Contents
Preface
Chapter 1: Introduction to Pandas
	What is Pandas?
		Pandas Options and Settings
		Pandas Data Frames
		Data Frames and Data Cleaning Tasks
		Alternatives to Pandas
	A Pandas Data Frame with a NumPy Example
	Describing a Pandas Data Frame
	Pandas Boolean Data Frames
		Transposing a Pandas Data Frame
	Pandas Data Frames and Random Numbers
	Reading CSV Files in Pandas
		Specifying a Separator and Column Sets in Text Files
		Specifying an Index in Text Files
	The loc() and iloc() Methods in Pandas
	Converting Categorical Data to Numeric Data
	Matching and Splitting Strings in Pandas
	Converting Strings to Dates in Pandas
	Working with Date Ranges in Pandas
	Detecting Missing Dates in Pandas
	Interpolating Missing Dates in Pandas
	Other Operations with Dates in Pandas
	Merging and Splitting Columns in Pandas
	Reading HTML Web Pages in Pandas
	Saving a Pandas Data Frame as an HTML Web Page
	Summary
Chapter 2: Introduction to Machine Learning
	What is Machine Learning?
		Types of Machine Learning
	Types of Machine Learning Algorithms
		Machine Learning Tasks
	Feature Engineering, Selection, and Extraction
	Dimensionality Reduction
		PCA
		Covariance Matrix
	Working with Datasets
		Training Data Versus Test Data
		What is Cross-validation?
	What is Regularization?
		Machine Learning and Feature Scaling
		Data Normalization versus Standardization
	The Bias-Variance Tradeoff
	Metrics for Measuring Models
		Limitations of R-Squared
		Confusion Matrix
		Accuracy versus Precision versus Recall
		The ROC Curve
	Other Useful Statistical Terms
		What is an F1 score?
		What is a p-value?
	What is Linear Regression?
		Linear Regression vs. Curve-Fitting
		When are Solutions Exact Values?
		What is Multivariate Analysis?
	Other Types of Regression
	Working with Lines in the Plane (optional)
	Scatter Plots with NumPy and Matplotlib (1)
		Why the Perturbation Technique is Useful
	Scatter Plots with NumPy and Matplotlib (2)
	A Quadratic Scatter Plot with NumPy and Matplotlib
	The Mean Squared Error (MSE) Formula
		A List of Error Types
		Non-linear Least Squares
	Calculating the MSE Manually
	Approximating Linear Data with np.linspace()
	Calculating MSE with np.linspace() API
	Summary
Chapter 3: Classifiers in Machine Learning
	What is Classification?
		What are Classifiers?
		Common Classifiers
		Binary versus Multiclass Classification
		Multilabel Classification
	What are Linear Classifiers?
	What is kNN?
		How to Handle a Tie in kNN
	What are Decision Trees?
	What are Random Forests?
	What are SVMs?
		Tradeoffs of SVMs
	What is Bayesian Inference?
		Bayes’ Theorem
		Some Bayesian Terminology
		What is MAP?
		Why Use Bayes’ Theorem?
	What is a Bayesian Classifier?
		Types of Naïve Bayes’ Classifiers
	Training Classifiers
	Evaluating Classifiers
	What are Activation Functions?
		Why Do We Need Activation Functions?
		How Do Activation Functions Work?
	Common Activation Functions
		Activation Functions in Python
	The ReLU and ELU Activation Functions
		The Advantages and Disadvantages of ReLU
		ELU
	Sigmoid, Softmax, and Hardmax Similarities
		Softmax
		Softplus
		Tanh
	Sigmoid, Softmax, and HardMax Differences
	What is Logistic Regression?
		Setting a Threshold Value
		Logistic Regression: Important Assumptions
		Linearly Separable Data
	Summary
Chapter 4: ChatGPT and GPT-4
	What is Generative AI?
		Important Features of Generative AI
		Popular Techniques in Generative AI
		What Makes Generative AI Unique
	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 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
		ChatGPT: Google “Code Red”
		ChatGPT versus Google Search
		ChatGPT Custom Instructions
		ChatGPT on Mobile Devices and Browsers
		ChatGPT and Prompts
		GPTBot
		ChatGPT Playground
	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 Gemini
		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
		Gemini
		CoPilot (OpenAI/Microsoft)
		Codex (OpenAI)
		Apple GPT
		PaLM-2
		Med-PaLM M
		Claude 2
	Llama 2
		How to Download Llama 2
		Llama 2 Architecture Features
		Fine Tuning Llama 2
	When Will GPT-5 Be Available?
	Summary
Chapter 5: Linear Regression with GPT-4
	What is Linear Regression?
	Examples of Linear Regression
	Metrics for Linear Regression
		Coefficient of Determination (R^2)
	Linear Regression with Random Data with GPT-4
	Linear Regression with a Dataset with GPT-4
	Descriptions of 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
	Describe Additional Model Diagnostics
	More Recommendations from GPT-4
	Summary
Chapter 6: Machine Learning Classifiers with GPT-4
	Machine Learning (According to GPT-4)
	What is Scikit-Learn?
	What is the kNN Algorithm?
	Selecting the Value of k in the kNN Algorithm
		Cross-Validation
		Bias-Variance Tradeoff
		Distance Metric
		Square Root Rule
		Domain Knowledge
		Even versus Odd k
		Computational Efficiency
		Diversity in the Dataset
	The Elbow Method for the kNN Algorithm
	A Machine Learning Model with the kNN Algorithm
	A Machine Learning Model with the Decision Tree Algorithm
	A Machine Learning Model with the Random Forest Algorithm
	A Machine Learning Model with the SVM Algorithm
	The Logistic Regression Algorithm
	The Naïve Bayes Algorithm
	The SVM Algorithm
	The Decision Tree Algorithm
	The Random Forest Algorithm
	Summary
Chapter 7: Machine Learning Clustering with GPT-4
	What is Clustering?
	Ten Clustering Algorithms
	Metrics for Clustering Algorithms
	K-means Clustering
	Hierarchical Clustering
	DBSCAN (Density-Based Spatial Clustering of Applications with Noise)
	What is the K-means Algorithm?
	What is the Hierarchical Clustering Algorithm?
	What is the DBSCAN Algorithm?
	A Machine Learning Model with the K-means Algorithm
	A Machine Learning Model with the Hierarchical Clustering Algorithm
	A Machine Learning Model with the DBSCAN Algorithm
	Summary
Chapter 8: 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
	Pie Charts 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
	Streamplots for Vector Fields
	Quiver Plots for Vector Fields
	Polar Plots
	Bar Charts with Seaborn
	Scatter Plots with Regression Lines Using Seaborn
	Heatmaps for Correlation Matrices 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
	Summary
Index