finelybook
Learn AI with Python: Explore machine learning and deep learning techniques for building smart AI systems using Scikit-learn, NLTK, NeuroLab, and Keras – 2nd Edition
Author(s): Gaurav Leekha (Author)
- Publisher finelybook 出版社: BPB Publications
- Publication Date 出版日期: January 2, 2026
- Edition 版本: Explore machine learning and deep learning techniques for building smart AI systems using Scikit-learn, NLTK, NeuroLab, and Keras – 2nd Edition
- Language 语言: English
- Print length 页数: 290 pages
- ISBN-10: 9365895006
- ISBN-13: 9789365895001
Book Description
This new edition takes you step by step into the world of AI, ML, and deep learning. You will learn how to preprocess and visualize data, perform feature engineering, and implement ML algorithms from scratch. The book further guides you through natural language processing with NLTK, building chatbots, developing image classifiers with CNNs, and improving model performance through fine-tuning and optimization.
By the end of this book, you will be confident in handling data, building intelligent systems, and deploying real-world AI applications using Python. Whether you are a student, a working professional, or a tech enthusiast, this book will equip you with the right skills and practical knowledge to begin your journey as an AI practitioner.
What you will learn
● Preprocess and visualize data for effective ML models.
● Implement ML algorithms from scratch using Python.
● Engineer features to enhance model accuracy and performance.
● Build intelligent chatbots and conversational AI applications with Python.
● Develop image classifiers using CNNs.
● Optimize and fine-tune ML models for real-world use.
● Apply natural language processing effectively using NLTK library.
● Create smart, data-driven solutions using AI techniques.
Who this book is for
This book is ideal for students, working professionals, and tech enthusiasts who want to build practical skills in AI. It is especially useful for software developers, data analysts, engineers, and researchers looking to create intelligent applications, chatbots, and predictive models using Python.
Table of Contents
1. Introduction to AI and Python
2. Machine Learning Basics
3. Preprocessing and Visualizing Data
4. Data Feature Engineering
5. Implementing ML Algorithms
6. Classification and Regression Using Supervised Learning
7. Clustering Using Unsupervised Learning
8. Solving Problems with Logic Programming
9. Natural Language Processing with Python
10. Implementing Speech Recognition with Python
11. Implementing Artificial Neural Network with Python
12. Implementing Reinforcement Learning with Python
13. Implementing Deep Learning and Convolutional Neural Network
14. Building Chatbots
15. Improving Performance of ML Model
