Statistics for machine learning : Techniques for exploring supervised, unsupervised, and reinforcement learning modules with Python and R /
Complex statistics in machine learning worry a lot of developers. Developing an accurate understanding of statistics will help you build robust machine learning models that are optimized for a given problem statement. This book will teach you everything you need to perform the complex statistical c...
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| Main Author: | |
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| Format: | Specialized reference book |
| Language: | English |
| Published: |
United Kingdom :
Packt,
2017.
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| Subjects: | |
| Online Access: | https://dlib.phenikaa-uni.edu.vn/handle/PNK/1639 |
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| Summary: | Complex statistics in machine learning worry a lot of developers. Developing an accurate understanding of statistics will help you build robust machine learning models that are optimized for a given problem statement.
This book will teach you everything you need to perform the complex statistical computations required for machine learning. You will learn about the statistics behind supervised learning, unsupervised learning, and reinforcement learning. The book will then take you through real-world examples that discuss the statistical side of machine learning to familiarize you with it. You will come across programs for performing tasks such as modeling, parameter fitting, regression, classification, density collection, working with vectors, matrices, and more.
By the end of this machine learning book, you’ll be well-versed with the statistics required for machine learning and will be able to apply your new skills to tackle problems related to this technology. |
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| Physical Description: | 424 tr. ; 27 cm. |
| ISBN: | 9781788295758 |