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Machine Learning Fundamentals. Use Python and scikit-learn to get up and running with the hottest developments in machine learning

Język publikacji: angielskim
Autor:
Hyatt Saleh
Machine Learning Fundamentals. Use Python and scikit-learn to get up and running with the hottest developments in machine learning Hyatt Saleh - okladka książki

Machine Learning Fundamentals. Use Python and scikit-learn to get up and running with the hottest developments in machine learning Hyatt Saleh - okladka książki

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As machine learning algorithms become popular, new tools that optimize these algorithms are also developed. Machine Learning Fundamentals explains you how to use the syntax of scikit-learn. You'll study the difference between supervised and unsupervised models, as well as the importance of choosing the appropriate algorithm for each dataset. You'll apply unsupervised clustering algorithms over real-world datasets, to discover patterns and profiles, and explore the process to solve an unsupervised machine learning problem.

The focus of the book then shifts to supervised learning algorithms. You'll learn to implement different supervised algorithms and develop neural network structures using the scikit-learn package. You'll also learn how to perform coherent result analysis to improve the performance of the algorithm by tuning hyperparameters.

By the end of this book, you will have gain all the skills required to start programming machine learning algorithms.

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O autorze książki

Hyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating from college as a business administrator. Since then, as a self-taught person, she not only works as a machine learning freelancer for many companies globally, but has also founded an artificial intelligence company that aims to optimize everyday processes. She has also authored Machine Learning Fundamentals, by Packt Publishing.

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