Pythonic AI

“Pythonic AI” is a book that teaches you how to build AI models using Python. It also includes practical projects in different domains so you can see how AI is used in the real world.

Besides teaching how to build AI models, the book also teaches how to understand and explore the opportunities that AI presents. It includes several hands-on projects that walk you through successful AI applications, explaining concepts like neural networks, computer vision, natural language processing (NLP), and generative models. Each project in the book also reiterates and reinforces the important aspects of Python scripting. You'll learn Python coding and how it can be used to build cutting-edge AI applications. The author explains each essential line of Python code in detail, taking into account the importance and difficulty of understanding.

By the end of the book, you will learn how to develop a portfolio of AI projects that will help you land your dream job in AI.

KEY FEATURES  

• Learn to code in Python and use Google Colab's hardware accelerators (GPU and TPU) to train and deploy AI models efficiently.
• Develop Convolutional Neural Networks (CNNs) using the TensorFlow 2 library for computer vision tasks.
• Develop sequence, attention-based, and Transformer models using the TensorFlow 2 library for Natural Language Processing (NLP) tasks.

WHAT YOU WILL LEARN

• Create neural network models using the TensorFlow 2 library.
• Develop Convolutional Neural Networks (CNNs) for computer vision tasks.
• Develop Sequence models for Natural Language Processing (NLP) tasks.
• Create Attention-based and Transformer models.
• Learn how to create Generative Adversarial Networks (GANs).

WHO THIS BOOK IS FOR

This book is for everyone who wants to learn how to build AI applications in Python, regardless of their experience level. Whether you're a student, a tech professional, a non-techie, or a technology enthusiast, this book will teach you the fundamentals of Python and AI, and show you how to apply them to real-world problems.

1. Python Kickstart: Concepts, Libraries, and Coding
2. Setting up AI Lab
3. Design My First Neural Network Model
4. Explore Designing CNN with TensorFlow
5. Develop CNN-based Image Classifier Apps
6. Train and Deploy Object Detection Models
7. Create a Text and Image Reader
8. Explore NLP for Advanced Text Analysis
9. Up and Running with Sequence Models
10. Using Sequence Models for Automated Text Classification
11. Create Attention and Transformer Models
12. Generating Captions for Images
13. Learn to Build GAN Models
14. Generate Artificial Faces Using GAN

Arindam Banerjee has been working in software development for more than 13 years, playing central roles as a technical leader and software engineer. He has architected and deployed numerous data-driven AI solutions to cater to both the data and AI requirements of the business and to help organizations succeed in their data endeavors without getting caught up in the hype. Currently, he is a Senior AI consultant at Ernst & Young GDS. He holds a master’s degree in Computer Science and Engineering from Vellore Institute of Technology, Vellore. He successfully got many certifications in AI technologies. Furthermore, the author participates as a speaker at international conferences and writes research papers on AI-related topics. He has filed nine patents till now.