Real-World Machine Learning
โ Henrik Brink Joseph W. Richards Mark Fetherolf
๐ Library
๐
2018
๐ Manning Publications
๐ English
โฆ LIBER โฆ
๐
Real-World Machine Learning
โ Scribed by Henrik Brink, Joseph Richards, Mark Fetherolf
- Publisher
- Manning Publications
- Year
- 2016
- Tongue
- English
- Leaves
- 266
- Category
- Library
โฌ Acquire This Volume
No coin nor oath required. For personal study only.
โฆ Synopsis
Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, youll build skills in data acquisition and modeling, classification, and regression. Youll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When youre done, youll be ready to successfully build, deploy, and maintain your own powerful ML systems.
Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems.
Predicting future behavior
Performance evaluation and optimization
Analyzing sentiment and making recommendations
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