Python 3 : using ChatGPT / GPT-4 / Oswald Campesato.

Format:

Book

Author/Creator:

Campesato, Oswald, author.

Series:

MLI generative AI series.

MLI Generative AI Series

Language:

English

Subjects (All):

Computer programming.

Python (Computer program language).

Video games--Programming.

Video games.

Artificial intelligence.

Physical Description:

1 online resource (xviii, 183 pages)

Place of Publication:

Boston, Massachusetts : Mercury Learning and Information, [2024]

Summary:

This book provides a comprehensive guide to using Python 3 in conjunction with ChatGPT and GPT-4, focusing on practical applications and programming techniques. It covers Python installation, basic syntax, data structures, and advanced topics such as NumPy and Pandas. The book aims to equip readers with the skills to effectively utilize Python for various computational tasks, including data analysis and algorithm development. It is intended for programmers, data scientists, and students looking to enhance their Python programming abilities, with a particular emphasis on integrating machine learning models into their workflows. Generated by AI.

This book is intended primarily for people who want to learn both Python 3 and how to use ChatGPT with Python. Chapter One begins with an introduction to fundamental aspects of Python programming, including various data types, number formatting, Unicode and UTF-8 handling, and text manipulation techniques. Later, the book covers loops, conditional logic, and reserved words in Python. You will also see how to handle user input, manage exceptions, and work with command-line arguments. Next, the text transitions to the realm of Generative AI, discussing its distinction from Conversational AI. Popular platforms and models, including ChatGPT, GPT-4, and their competitors, are presented to give readers an understanding of the current AI landscape. The book also sheds light on the capabilities of ChatGPT, its strengths, weaknesses, and potential applications. In addition, you will learn how to generate a variety of Python 3 code samples via ChatGPT using the "Code Interpreter" plugin. Code samples and figures from the book are available for downloading. In essence, the book provides a modest bridge between the worlds of Python programming and AI, aiming to equip readers with the knowledge and skills to navigate both domains confidently.

Contents:

Cover

Title Page

Copyright Page

Dedication

Contents

Preface

Chapter 1: Introduction to Python 3

Tools for Python

easy_install and pip

virtualenv

IPython

Python Installation

Setting the PATH Environment Variable (Windows Only)

Launching Python on Your Machine

The Python Interactive Interpreter

Python Identifiers

Lines, Indentation, and Multilines

Quotation and Comments in Python

Saving Your Code in a Module

Some Standard Modules in Python

The help() and dir() Functions

Compile Time and Runtime Code Checking

Simple Data Types in Python

Working With Numbers

Working With Other Bases

The chr() Function

The round() Function in Python

Formatting Numbers in Python

Working With Fractions

Unicode and UTF-8

Working With Unicode

Working With Strings

Comparing Strings

Formatting Strings in Python

Slicing and Splicing Strings

Testing for Digits and Alphabetic Characters

Search and Replace a String in Other Strings

Remove Leading and Trailing Characters

Printing Text without NewLine Characters

Text Alignment

Working With Dates

Converting Strings to Dates

Exception Handling in Python

Handling User Input

Command-Line Arguments

Summary

Chapter 2: Conditional Logic, Loops, and Functions

Precedence of Operators in Python

Python Reserved Words

Working with Loops in Python

Python for Loops

A for Loop with try/except in Python

Numeric Exponents in Python

Nested Loops

The split() Function With for Loops

Using the split() Function to Compare Words

Using the split() Function to Print Justified Text

Using the split() Function to Print Fixed-Width Text

Using the split() Function to Compare Text Strings

Using the split() Function to Display Characters in a String

The join() Function.

Python while Loops

Conditional Logic in Python

The break/continue/pass Statements

Comparison and Boolean Operators

The in/not in/is/is not Comparison Operators

The and, or, and not Boolean Operators

Local and Global Variables

Uninitialized Variables and the Value None

Scope of Variables

Pass by Reference Versus Value

Arguments and Parameters

Using a while loop to Find the Divisors of a Number

Using a while loop to Find Prime Numbers

User-Defined Functions in Python

Specifying Default Values in a Function

Returning Multiple Values From a Function

Functions With a Variable Number of Arguments

Lambda Expressions

Recursion

Calculating Factorial Values

Calculating Fibonacci Numbers

Calculating the GCD of Two Numbers

Calculating the LCM of Two Numbers

Chapter 3: Python Data Structures

Working With Lists

Lists and Basic Operations

Reversing and Sorting a List

Lists and Arithmetic Operations

Lists and Filter-Related Operations

Sorting Lists of Numbers and Strings

Expressions in Lists

Concatenating a List of Words

The BubbleSort in Python

The Python range() Function

Counting Digits, Uppercase, and Lowercase Letters

Arrays and the append() Function

Working with Lists and the split() Function

Counting Words in a List

Iterating Through Pairs of Lists

Other List-Related Functions

Using a List as a Stack and a Queue

Working With Vectors

Working With Matrices

The NumPy Library for Matrices

Queues

Tuples (Immutable Lists)

Sets

Dictionaries

Creating a Dictionary

Displaying the Contents of a Dictionary

Checking for Keys in a Dictionary

Deleting Keys From a Dictionary

Iterating Through a Dictionary

Interpolating Data From a Dictionary

Dictionary Functions and Methods

Dictionary Formatting.

Ordered Dictionaries

Sorting Dictionaries

Python Multidictionaries

Other Sequence Types in Python

Mutable and Immutable Types in Python

The type() Function

Chapter 4: Introduction to NumPy and Pandas

What Is NumPy?

Useful NumPy Features

What Are NumPy arrays?

Working With Loops

Appending Elements to Arrays (1)

Appending Elements to Arrays (2)

Multiply Lists and Arrays

Doubling the Elements in a List

Lists and Exponents

Arrays and Exponents

Math Operations and Arrays

Working With "-1" Subranges With Vectors

Working With "-1" Subranges With Arrays

Other Useful NumPy Methods

Arrays and Vector Operations

NumPy and Dot Products (1)

NumPy and Dot Products (2)

NumPy and the "Norm" of Vectors

NumPy and Other Operations

NumPy and the reshape() Method

Calculating the Mean and Standard Deviation

Calculating Mean and Standard Deviation

What Is Pandas?

Pandas DataFrames

Dataframes and Data Cleaning Tasks

A Labeled Pandas DataFrame

Pandas Numeric DataFrames

Pandas Boolean DataFrames

Transposing a Pandas DataFrame

Pandas DataFrames and Random Numbers

Combining Pandas DataFrames (1)

Combining Pandas DataFrames (2)

Data Manipulation With Pandas DataFrames (1)

Data Manipulation With Pandas DataFrames (2)

Data Manipulation With Pandas DataFrames (3)

Pandas DataFrames and CSV Files

Pandas DataFrames and Excel Spreadsheets

Select, Add, and Delete Columns in DataFrames

Pandas DataFrames and Scatterplots

Pandas DataFrames and Simple Statistics

Useful One-Line Commands in Pandas

Chapter 5: 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 Objective.

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

Plugins, Advanced Data Analysis, and Code Whisperer

Plugins

Advanced Data Analysis

Advanced Data Analysis Versus Claude-2

Advanced Data Analysis and Charts and Graphs

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

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 GPT

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?

Chapter 6: ChatGPT and Python Code

Simple Calculator

Simple File Handling

Simple Web Scraping

Basic Chat Bot

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

Index.

Notes:

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Description based on print version record.

ISBN:

9781501518737