Download this EPUB book: Learn AI with Python: Explore Machine Learning and Deep Learning techniques for Building Smart AI Systems Using Scikit-Learn, NLTK, NeuroLab, and Keras by Gaurav Leekha
About the Author
Gaurav Leekha is a Deep Learning researcher. He has 7 years of academic experience of teaching technical courses along with 5+ years of technical content creation as a freelancer on variety of topics related to Machine Learning, Deep Learning, Artificial Intelligence, and Web Development Technologies.
He has authored a few research papers published in renowned journals. He is also the reviewer of prominent journals and has been the technical reviewer for various online courses. He has also earned multiple certifications in the field of machine learning and deep learning.
Outside work, Gaurav likes to cook food for his family, play with his eight-year-old son and practice vipassana meditation.
Over the 10 chapters in this book, you will learn the following:
Chapter 1 covers the basics of Artificial Intelligence and explains all the important terms and definitions. It also explains various fields of study in AI and applications of AI in various industries. It will assist you in installing the Python programming language on different platforms.
Chapter 2 covers the basics of Machine Learning and its different learning styles. It also introduces you to the most popular machine learning algorithms and their implementation using Python.
Chapter 3 deals with supervised machine learning tasks namely Classification and Regression. It covers various steps to build a classifier and regressor using Python. It also discusses various performance metrics used to evaluate classification and regression models.
Chapter 4 deals with unsupervised machine learning tasks namely Clustering. It covers some important ML clustering algorithms and their implementation using Python. It also discusses various metrics used to evaluate the performance of clustering algorithms.
Chapter 5 covers logic programming with some implementation examples useful for solving problems in the real-life domain.
Chapter 6 discusses, in-depth, what is Natural Language Processing (NLP) and how to implement it in Python. It introduces you to Python’s Natural Language Toolkit (NLTK). It then shows how you can implement various important concepts of NLP using NLTK.
Chapter 7 describes the working of an automatic speech recognition (ASR) system. It also covers various steps to build a classifier and regressor using Python.
Chapter 8 discusses Artificial Neural Network (ANN) in detail. It then covers building some useful neural networks such as Single layer neural networks, Multilayer neural networks, etc., in Python.
Chapter 9 is a key chapter that discusses, in detail, reinforcement learning and its building blocks namely agent and environment. It describes how to construct an environment and agent using the Python programming language.
Chapter 10 is another key chapter, covering the basics of deep learning and convolutional neural networks (CNNs). It then explains the evolution of CNN and how it provides complicated object detection in images. It also explains how to build an image classifier using CNN in Python.
About the book:
Publisher : BPB Publications (18 October 2021)
Language : English
Pages : 270 , EPUB
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