JQUERY CODING AND DEEP LEARNING WITH PYTHON MADE SIMPLE: A BEGINNER’S GUIDE TO PROGRAMMING - 2 BOOKS IN 1

✍ Scribed by STOKES, MARK

• Publisher: Independently Published
• Year: 2024
• Tongue: English
• Leaves: 178
• Category: Library

✦ Synopsis

"jQuery Coding Made Simple: A Beginner's Guide to Programming" is a comprehensive and accessible ebook that introduces readers to the world of jQuery and empowers them to build dynamic and interactive web applications. Whether you're a novice programmer or an experienced developer looking to expand your skill set, this book provides a step-by-step approach to learning jQuery in an easy-to-understand language.

With a focus on practical examples and hands-on exercises, this ebook takes you on a journey through the core concepts of jQuery. Starting from the basics, you'll learn how to select and manipulate HTML elements, handle events, create animations, validate forms, implement responsive design techniques, and leverage the power of plugins and libraries. Each chapter delves into a specific aspect of jQuery, ensuring a comprehensive understanding of the framework.

✦ Table of Contents

Chapter 1: Introduction to jQuery
Chapter 2: Getting Started with jQuery
Chapter 3: Selectors and Filters in jQuery
Chapter 4: Manipulating DOM Elements with jQuery
Chapter 5: Event Handling in jQuery
Chapter 6: jQuery Effects and Animations
Chapter 7: Working with AJAX in jQuery
Chapter 8: jQuery and Form Validation
Chapter 9: Responsive Web Design with jQuery
Chapter 10: jQuery Plugins and Libraries
Chapter 11: Best Practices in jQuery Coding
Chapter 12: Debugging and Troubleshooting in jQuery
Chapter 13: Advanced jQuery Techniques
Chapter 14: Building Interactive Web Applications with jQuery
Chapter 15: jQuery and Mobile Development
DEEP LEARNING WITH PYTHON
Chapter 1: Introduction to Deep Learning
Chapter 2: Getting Started with Python
Chapter 3: Understanding Neural Networks
Chapter 4: Basics of Machine Learning
Chapter 5: Building Your First Neural Network
Chapter 6: Deep Learning Libraries and Tools
Chapter 7: Data Preparation and Preprocessing
Chapter 8: Training and Evaluating Neural Networks
Chapter 9: Convolutional Neural Networks
Chapter 10: Recurrent Neural Networks
Chapter 11: Generative Adversarial Networks
Chapter 12: Natural Language Processing
Chapter 13: Computer Vision Applications
Chapter 14: Reinforcement Learning
Chapter 15: Deep Learning in the Real World
Chapter 16: FAQ - Deep Learning with Python Programming