Data Science Bookcamp: Five real-world Python projects

Author: Leonard Apeltsin

Publisher Finelybook 出版社：Manning Publications; 1st edition (1 Jan. 2022)

Language 语言：English

pages 页数：600 pages

ISBN-10 书号：1617296252

ISBN-13 书号：9781617296253**Book Description**

Learn data science with Python Author: building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science.

In Data Science Bookcamp you will learn:

Techniques for computing and plotting probabilities

Statistical analysis using Scipy

How to organize datasets with clustering algorithms

How to visualize complex multi-variable datasets

How to train a decision tree machine learning algorithm

In Data Science Bookcamp you’ll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career.

A data science project has a lot of moving parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations working together harmoniously. This unique book guides you through five realistic projects, including tracking disease outbreaks from news headlines, analyzing social networks, and finding relevant patterns in ad click data.

Data Science Bookcamp doesn’t stop with surface-level theory and toy examples. As you work through each project, you’ll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don’t quite fit the model you’re building. You’ll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you’ll be confident in your skills because you can see the results.

What’s inside

Web scraping

Organize datasets with clustering algorithms

Visualize complex multi-variable datasets

Train a decision tree machine learning algorithm

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