Abhijit Ghatak

Machine Learning with R (eBook, PDF)

• Format: PDF

Produktbeschreibung

¿Help readers understand the mathematical interpretation of learning algorithms

Teach the basics of linear algebra, probability, and data distributions and how they are essential in formulating a learning algorithm

Help readers construct and modify their own learning algorithms, such as ridge and lasso regression, decision trees, boosted trees, k-nearest neighbors, etc

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 210
• Erscheinungstermin: 23. November 2017
• Englisch
• ISBN-13: 9789811068089
• Artikelnr.: 53058811

Autorenporträt

Abhijit Ghatak is a Data Scientist and holds an ME in Engineering and MS in Data Science from Stevens Institute of Technology, USA. He started his career as a submarine engineer officer in the Indian Navy and worked on multiple data-intensive projects involving submarine operations and construction. He has worked in academia, technology companies and as a research scientist in the area of Internet of Things (IoT) and pattern recognition for the European Union (EU). He has published in the areas of engineering and machine learning and is presently a consultant in the area of pattern recognition and data analytics. His areas of research include IoT, stream analytics and design of deep learning systems.

Inhaltsangabe

Chapter 1. Linear Algebra, Numerical Optimization and it's Applications in Machine Learning.- Chapter 2. Probability and Distributions.- Chapter 3.Introduction to Machine Learning.- Chapter 4. Regression.- Chapter 5. Classification.- Chapter 6. Clustering.

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