Step-by-step instructions for Machine Learning

Step-by-step instructions for Machine Learning

You have a complex problem with a large amount of data and many variables? You know that machine learning would be the best approach to solve this problem, but you have never used it before? How do you handle chaotic, incomplete and unformatted data? How do you choose the right data model?
Does this act as a deterrent? Do not get discouraged. A systematic approach will help you master your task.
With the help of the free e-book you will learn step-by-step the basic knowledge up to advanced methods and algorithms. The e-book is available in English language:
Section 1: Machine Learning Basics
Learn the basics of machine learning, including supervised and unsupervised learning, algorithm selection and practical examples.

Section 2: Getting Started with Machine Learning
Discover the Machine Learning Workflow step by step with a health app. This section explains data access, data pre-processing, derived radio Section 1: Machine Learning Basics
Learn the basics of machine learning, including supervised and unsupervised learning, algorithm selection and practical examples.

Section 2: Getting Started with Machine Learning
Discover the Machine Learning Workflow step by step with a health app. This section explains data access, data preprocessing, derived functions, and the resulting data preparation.

Section 3: Using Unsupervised Learning
Explore the possibilities of clustering algorithms and apply dimension reduction to improve model performance.

Section 4: Apply supervised learning
Classification and regression algorithms help to improve the models.

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