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Supervised Learning with Python: Concepts and Practical Implementation Using Python
Paperback
General ComputersProbability & StatisticsProgramming
Publisher Price: $54.99
ISBN13: 9781484261552
Publisher: Apress
Published: Oct 8 2020
Pages: 372
Weight: 1.21
Height: 0.81 Width: 6.14 Depth: 9.21
Language: English
Gain a thorough understanding of supervised learning algorithms by developing use cases with Python. You will study supervised learning concepts, Python code, datasets, best practices, resolution of common issues and pitfalls, and practical knowledge of implementing algorithms for structured as well as text and images datasets.
What You'll Learn
- Review the fundamental building blocks and concepts of supervised learning using Python
- Develop supervised learning solutions for structured data as well as text and images
- Solve issues around overfitting, feature engineering, data cleansing, and cross-validation for building best fit models
- Understand the end-to-end model cycle from business problem definition to model deployment and model maintenance
- Avoid the common pitfalls and adhere to best practices while creating a supervised learning model using Python
Data scientists or data analysts interested in best practices and standards for supervised learning, and using classification algorithms and regression techniques to develop predictive models.
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