Machine Learning_ Step-by-Step Guide To Implement Machine Learning Algorithms with Python

“Machine Learning: Step-by-Step Guide To Implement Machine Learning Algorithms with Python” is a comprehensive book that provides a step-by-step guide to learning and implementing machine learning algorithms using the Python programming language. The book is centered around providing a deep understanding of machine learning concepts and their practical applications using Python as a tool for developing and evaluating models.

Expected contents of the book include:

Introduction to Machine Learning: The book provides a definition of machine learning and its importance, and explains the types of machine learning and their applications.

Python Basics: A quick introduction to the Python language, including basic data, control flow, and functions.

Exploring Datasets: The book explains how to explore and analyze datasets using the Python pandas library.

Data Preparation: The book covers data preparation processes such as cleaning, transforming, and dividing the data into training and test sets.

Implementing machine learning algorithms: The book includes implementing popular machine learning algorithms such as linear regression, artificial neural networks, suggestion support, etc., using the Python scikit-learn library.

Model Evaluation: The book explains how to evaluate and improve the performance of models using various performance metrics and optimization techniques.

Practical applications: The book covers some current studies and practical applications of machine learning in various fields such as data analysis, classification, prediction, and others.

The book takes an interactive and practical approach, providing practical examples and interactive exercises that help the reader better understand the concepts and apply them practically using Python.