Description
- Understand machine learning algorithms, models, and core machine learning concepts
- Classify examples with classifiers, and quantify examples with regressors
- Realistically assess performance of machine learning systems
- Use feature engineering to smooth rough data into useful forms
- Chain multiple components into one system and tune its performance
- Apply machine learning techniques to images and text
- Connect the core concepts to neural networks and graphical models
- Leverage the Python scikit-learn library and other powerful tools
Author: Mark Fenner
Publisher: Addison-Wesley Professional
Published: 08/16/2019
Pages: 592
Binding Type: Paperback
Weight: 2.00lbs
Size: 9.00h x 6.90w x 1.30d
ISBN13: 9780134845623
ISBN10: 0134845625
BISAC Categories:
- Computers | Data Science | Data Analytics
- Computers | Languages | Python
- Computers | Artificial Intelligence | General
About the Author
Dr. Mark Fenner, owner of Fenner Training and Consulting, LLC, has taught computing and mathematics to diverse adult audiences since 1999, and holds a PhD in computer science. His research has included design, implementation, and performance of machine learning and numerical algorithms; developing learning systems to detect user anomalies; and probabilistic modeling of protein function.