Think AI: Explore the flavours of Machine Learning, Neural Networks, Computer Vision and NLP with powerful Python libraries (English Edition)
Author: Swapnali Joshi Naik
Publisher Finelybook 出版社：BPB Publications (June 28, 2022)
pages 页数：274 pages
Develop AI based real-world Applications
● Provides a practical understanding of AI, including its concepts, tools and techniques.
● Includes step-Author:-Author:-step instructions for implementing machine learning and deep learning algorithms and features.
● Complex datasets and examples are used to expose mathematical illustrative and pseudo-coded examples.
"Think AI" is a rapid-learning book that covers a wide range of Artificial Intelligence topics, including Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing. Most popular Python libraries and toolkits are applied to develop intelligent and thoughtful applications.
With a solid grasp of python programming and mathematics, you may use this book's statistical models and AI algorithms to meet AI needs and data insight issues. Each chapter in this book guides you swiftly through the core concepts and then directly to their implementation using Python toolkits. This book covers the techniques and skill sets required for data collection, pre-processing, installing libraries, preparing data models, training and deploying the models, and optimising model performance.
The book guides you through the OpenCV toolkit for real-time picture recognition and detection, allowing you to work with computer vision. The book describes how to analyse linguistic data and conduct text mining using the NLTK toolbox and provides a brief overview of NLP ideas. Throughout the book, you will utilise major Python libraries and toolkits such as pandas, TensorFlow, scikit-learn, and matplotlib.
What you will learn
● Work with Jupyter and various Python libraries, including scikit-learn, NLTK, and TF.
● Build and implement ML models and neural networks using TensorFlow and Keras.
● Utilize OpenCV for real-time image processing, face detection, and face recognition.
● Know how to interact and process textual data using NLTK toolkit.
● Deep dive on Exploratory Data Analysis (EDA) with pandas, matplotlib and seaborn.
Who this book is for
Whether you're a student, newbie or an existing AI developer, this book will help you get up to speed with various domains of AI, including ML, Deep Learning and NLP. Knowing the basics of python and understanding mathematics will be beneficial.
Table of Contents
1. Introducing Artificial Intelligence
2. Essentials of Python and Data Analysis
3. Data Preparation and Machine Learning
4. Computer Vision using OpenCV
5. Fundamentals of Neural Networks and Deep Learning
6. Natural Language Processing