<div> <h3>About This Book</h3> <ul><li>Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark</li> <li>Comprehensive practical solutions taking you into the future of machine learning</li> <li>Go a step further and integrate
Practical Machine Learning
β Scribed by Ted Dunning and Ellen Friedman
- Publisher
- OReilly Media
- Year
- 2014
- Tongue
- English
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Anomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what suspects you’re looking for. This O’Reilly report uses practical example to explain how the underlying concepts of anomaly detection work.
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Machine learning has become the new black. The challenge in todayβs world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learnin