Build AI applications using Python to intelligently interact with the world around you.
Key Features
● Covers the practical aspects of Machine Learning and Deep Learning concepts with the help of this example-rich guide to Python.
● Includes graphical illustrations of Natural Language Processing and its implementation in NLTK.
● Covers deep learning models such as R-CNN and YOLO for object recognition and teaches how to build an image classifier using CNN.
Description
The book ‘Learn AI with Python’ is intended to provide you with a thorough understanding of artificial intelligence as well as the tools necessary to create your intelligent applications.
This book introduces you to artificial intelligence and walks you through the process of establishing an AI environment on a variety of platforms. It dives into machine learning models and various predictive modeling techniques, including classification, regression, and clustering. Additionally, it provides hands-on experience with logic programming, ASR, neural networks, and natural language processing through real-world examples and fully functional Python implementation. Finally, the book deals with profound models of learning such as R-CNN and YOLO. Object detection in images is also explained in detail using Convolutional Neural Networks (CNNs), which are also explained.
By the end of this book, you will have a firm grasp of machine learning and deep learning techniques, as well as a steered methodology for formulating and solving related problems.
What you will learn
● Learn to implement various machine learning and deep learning algorithms to achieve smart results.
● Understand how ML algorithms can be applied to real-life applications.
● Explore logic programming and learn how to use it practically to solve real-life problems.
● Learn to develop different types of artificial neural networks with Python.
● Understand reinforcement learning and how to build an environment and agents using Python.
● Work with NLTK and build an automatic speech recognition system.
Who this book is for
This book is for anyone interested in learning about artificial intelligence and putting it into practice with Python. This book is also valuable for intermediate Machine Learning practitioners as a reference guide. Readers should be familiar with the fundamental understanding of Python programming and machine learning techniques.
Table of Contents
1. Introduction to AI and Python
2. Machine Learning and Its Algorithms
3. Classification and Regression Using Supervised Learning
4. Clustering Using Unsupervised Learning
5. Solving Problems with Logic Programming
6. Natural Language Processing with Python
7. Implementing Speech Recognition with Python
8. Implementing Artificial Neural Network (ANN) with Python
9. Implementing Reinforcement Learning with Python
10. Implementing Deep Learning and Convolutional Neural Network
