Machine learning algorithms reference guide for popular algorithms for data science and machine learning
As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading str...
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| Format: | E-Book Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Birmingham
PACKT Publishing
2017
Packt Pub Packt Publishing, Limited Packt Publishing Limited |
| Ausgabe: | 1st ed. |
| Schlagworte: | |
| ISBN: | 9781785889622, 1785889621, 1785884514, 9781785884511 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. In this book you will learn all the important Machine Learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. A few famous algorithms that are covered in this book are Linear regression, Logistic Regression, SVM, Naive Bayes, K-Means, Random Forest, TensorFlow, and Feature engineering. In this book you will also learn how these algorithms work and their practical implementation to resolve your problems. This book will also introduce you to the Natural Processing Language and Recommendation systems, which help you run multiple algorithms simultaneously. On completion of the book you will have mastered selecting Machine Learning algorithms for clustering, classification, or regression based on for your problem. |
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| Bibliographie: | Includes bibliographical references and index |
| ISBN: | 9781785889622 1785889621 1785884514 9781785884511 |
| DOI: | 10.0000/9781785884511 |