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bonaccorso g machine learning algorithms 2ed 2018

Type:: E-books
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Size:: 65.3 MB
Uploaded On:: Oct. 31, 2019, 9:26 a.m.
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Info Hash:: 93B5BA831CC55BCA7924F59B0FE4B0881F60FD23

Textbook in PDF format Key Features Explore statistics and complex mathematics for data-intensive applications. Discover new developments in EM algorithm, PCA, and bayesian regression. Study patterns and make predictions across various datasets. Book Description Machine learning has gained tremendous popularity for its powerful and fast predictions with large datasets. However, the true forces behind its powerful output are the complex algorithms involving substantial statistical analysis that churn large datasets and generate substantial insight. This second edition of Machine Learning Algorithms walks you through prominent development outcomes that have taken place relating to machine learning algorithms, which constitute major contributions to the machine learning process and help you to strengthen and master statistical interpretation across the areas of supervised, semi-supervised, and reinforcement learning. Once the core concepts of an algorithm have been covered, you’ll explore real-world examples based on the most diffused libraries, such as scikit-learn, NLTK, TensorFlow, and Keras. You will discover new topics such as principal component analysis (PCA), independent component analysis (ICA), Bayesian regression, discriminant analysis, advanced clustering, and gaussian mixture. By the end of this book, you will have studied machine learning algorithms and be able to put them into production to make your machine learning applications more innovative

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Bonaccorso G. Machine Learning Algorithms...2ed 2018.pdf 65.3 MB

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bonaccorso g machine learning algorithms 2ed 2018

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