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Home> Data> GPT/LLMs> Python 3 Using ChatGPT / GPT-4
Python 3 Using ChatGPT / GPT-4
Python 3 Using ChatGPT / GPT-4

Python 3 Using ChatGPT / GPT-4: Harnessing AI for Efficient Python Programming

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Profile Icon Mercury Learning and InformationProfile Icon Oswald Campesato
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₹4051.99
eBookAug 2024202 pages1st Edition
eBook
₹4051.99
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Profile Icon Mercury Learning and InformationProfile Icon Oswald Campesato
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₹4051.99
eBookAug 2024202 pages1st Edition
eBook
₹4051.99
eBook
₹4051.99

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Key benefits

  • Detailed coverage of Python 3 basics and advanced topics
  • Practical examples integrating ChatGPT/GPT-4
  • Real-world applications for hands-on learning

Description

This book is for people who want to learn Python 3 and how to use ChatGPT with Python. It starts with an introduction to Python programming, covering data types, number formatting, Unicode handling, and text manipulation. The book then covers loops, conditional logic, reserved words, user input, exception management, and command-line arguments.The journey continues into Generative AI, discussing its distinction from Conversational AI. Popular platforms like ChatGPT and GPT-4 are explored, along with their strengths, weaknesses, and potential applications. The book shows how to generate Python 3 code samples via ChatGPT using the “Code Interpreter” plugin.Understanding these concepts is crucial for navigating Python and AI. This book transitions readers from basic Python programming to advanced AI applications, blending theory with practical skills. Companion files with code samples and figures enhance learning, making this an essential resource for mastering Python and ChatGPT.

Who is this book for?

Ideal for Python enthusiasts, programmers, and AI developers looking to integrate ChatGPT/GPT-4 into their workflow. A basic understanding of Python is recommended. No prior AI knowledge is required.

What you will learn

  • Understand Python basics
  • Implement AI-driven coding
  • Handle data structures
  • Utilize NumPy and Pandas
  • Generate AI prompts
  • Create advanced Python projects

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date :Aug 12, 2024
Original Publication date :Dec 12, 2023
Length:202 pages
Edition :1st
Language :English
ISBN-13 :9781836647867
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Product Details

Publication date :Aug 12, 2024
Original Publication date :Dec 12, 2023
Length:202 pages
Edition :1st
Language :English
ISBN-13 :9781836647867
Category :
Concepts :

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Table of Contents

7 Chapters
Chapter 1: Introduction to Python 3Chevron down iconChevron up icon
Chapter 1: Introduction to Python 3
Tools for Python
Python Installation
Setting the PATH Environment Variable (Windows Only)
Launching Python on Your Machine
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 Fractions
Unicode and UTF-8
Working With Unicode
Working With Strings
Slicing and Splicing Strings
Search and Replace a String in Other Strings
Remove Leading and Trailing Characters
Printing Text without NewLine Characters
Text Alignment
Working With Dates
Exception Handling in Python
Handling User Input
Command-Line Arguments
Summary
Chapter 2: Conditional Logic, Loops, and FunctionsChevron down iconChevron up icon
Chapter 2: Conditional Logic, Loops, and Functions
Precedence of Operators in Python
Python Reserved Words
Working with Loops 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
Local and Global Variables
Scope of Variables
Pass by Reference Versus Value
Arguments and Parameters
Using a while loop to Find the Divisors of a Number
User-Defined Functions in Python
Specifying Default Values in a Function
Functions With a Variable Number of Arguments
Lambda Expressions
Recursion
Summary
Chapter 3: Python Data StructuresChevron down iconChevron up icon
Chapter 3: Python Data Structures
Working With Lists
Sorting Lists of Numbers and Strings
Expressions in Lists
Concatenating a List of Words
The BubbleSort in Python
The Python range() Function
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
Dictionary Functions and Methods
Dictionary Formatting
Ordered Dictionaries
Other Sequence Types in Python
Mutable and Immutable Types in Python
The type() Function
Summary
Chapter 4: Introduction to NumPy and PandasChevron down iconChevron up icon
Chapter 4: Introduction to NumPy and Pandas
What Is NumPy?
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?
A Labeled Pandas DataFrame
Pandas Numeric DataFrames
Pandas Boolean DataFrames
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
Summary
Chapter 5: ChatGPT and GPT-4Chevron down iconChevron up icon
Chapter 5: ChatGPT and GPT-4
What Is Generative AI?
Conversational AI Versus Generative AI
Is DALL-E Part of Generative AI?
Are ChatGPT-3 and GPT-4 Part of Generative AI?
DeepMind
OpenAI
Cohere
Hugging Face
AI21
InflectionAI
Anthropic
What Is Prompt Engineering?
What Is ChatGPT?
Plugins, Advanced Data Analysis, and Code Whisperer
Detecting Generated Text
Concerns About ChatGPT
Sample Queries and Responses From ChatGPT
Alternatives to ChatGPT
What Is InstructGPT?
VizGPT and Data Visualization
What Is GPT-4?
ChatGPT and GPT-4 Competitors
LlaMa-2
When Is GPT-5 Available?
Summary
Chapter 6: ChatGPT and Python CodeChevron down iconChevron up icon
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
Summary
IndexChevron down iconChevron up icon
Index

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About the authors

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Profile icon Mercury Learning and Information
Mercury Learning and Information
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MERCURY LEARNING and INFORMATION publishes content in the areas of science and medicine, technology and computing, engineering, and mathematics designed for the professional/reference, trade, library, higher education, career school, and online training markets.
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See other products by Mercury Learning and Information
Profile icon Oswald Campesato
Oswald Campesato
Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty books including Google Gemini for Python, Data Cleaning, and GPT-4 for Developers (all Mercury Learning).
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