Machine Learning Fundamentals
As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains the scikit-learn API, which is a package created to facilitate the process of building machine learning applications. By explaining the differences between supervised and unsupervised models and by applying some popular algorithms to real-life datasets, this course gives you the skills and confidence to start programming machine learning algorithms.
Offered by
Difficulty Level
Intermediate
Completion Time
8h
Language
English
About Book
Who Is This Book For?
Machine Learning Fundamentals is designed for developers who are new to the field of machine learning and want to learn how to use the scikit-learn library to develop machine learning algorithms. You must have some knowledge and experience in Python programming, but you do not need any prior knowledge of scikit-learn or machine learning algorithms.
Machine Learning Fundamentals
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 8h total length
Introduction to sciki-learn
Unsupervised Learning: Real-life Applications
Supervised Learning: Key Steps
Supervised Learning Algorithms: Predict Annual Income
Artificial Neural Networks: Predict of Annual Income
Building Your Own Program
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