This step-by-step guide is aimed at beginners who know a little Python and are looking for a quick, fast-paced introduction. Author Alex Galea explores machine learning models with real datasets. The book ends by showing how easy it can be to scrape and gather data from the open web.
<ASIN:1789532027>
Author: Alex Galea Publisher: Packt Publishing Date: June 2018 Pages: 194 ISBN: 978-1789532029 Print: 1789532027 Kindle: B07DNJ9KKL Audience: Python developers Level: Introductory Category: Data Science
- Identify potential areas of investigation and perform exploratory data analysis
- Plan a machine learning classification strategy and train classification models
- Use validation curves and dimensionality reduction to tune and enhance your models
- Scrape tabular data from web pages and transform it into Pandas DataFrames
- Create interactive, web-friendly visualizations to clearly communicate your findings
For recommendations of books on big data, see Reading Your Way Into Big Data. For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.
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SQL Server Query Tuning and Optimization (Packt)
Author: Benjamin Nevarez Publisher: Packt Publishing Pages: 446 ISBN: 9781803242620 Print: 1803242620 Kindle: B0B42SVBFY Audience: Intermediate to advanced DBAs and developers Rating: 4.7 Reviewer: Ian Stirk
This book aims to give you the tools and knowledge to get peak performance from your que [ ... ]
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Author: Jason Hales, Almantas Karpavicius and Mateus Viegas Publisher: Packt Date: September 2022 Pages: 780 ISBN: 978-1800566491 Print: 1800566492 Kindle: B0BGRBDJLS Audience: C# developers Rating: 4 Reviewer: Mike James C# is not the language it once was - time for a revival?
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