Embark on a journey into the dynamic world of machine learning, an innovative application of artificial intelligence (AI). In this Python-based tutorial, you will delve into the intricacies of machine learning and gain practical knowledge and insights. Here are some of its key features

Basic Python

• Learn what Python is, what it means, and why it was chosen.
• Learn the basics of loops, object-oriented programming, functions, and file processing.

Machine learning and AI

• Understand the basic concepts of artificial intelligence and its applications.
• Explore machine learning concepts, including supervised and unsupervised learning.
• Discover key modules like Scikit Learn, Numpy, Pandas, Matplotlib, and more.
• Understand key concepts such as regression analysis, clustering, K-means and SVM classification.

Implementation in Python

• Use Python to code simple linear regression, multiple regression, SVM classification, K-means clustering, and decision tree classification.

Machine Learning Cookbook

• Check out our extensive cookbooks on various aspects of machine learning.
• Table of contents, vectors, matrices, arrays.
• Data management, numerical and categorical data processing.
• Text, date, time and image processing.
• Dimensionality reduction through feature extraction and selection.
• Evaluation and selection of models.
• Detailed tutorials on linear regression, trees, forests, K-nearest neighbors, logistic regression, SVM, Naive Bayes, clustering and neural networks.
• Techniques for saving and loading trained models.