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Source code Errata Book Forum Improve Your Data Science Skills 🎙️ Leonard Apeltsin interviewed 🎙️ NLP Analysis of Large Text Datasets Conducted by Dr. Leonard Apeltsin Basic Probability and Statistical Analysis Using SciPy Computing Travel Probabilities Using Matrix Multiplication Register your pBook for a free eBook Clustering Data into Groups, Part 1 Clustering Data into Groups, Part 2 Clustering Data into Groups, Part 3 more

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Data Science Bookcamp you own this product

Five real-world Python projects

6 reviews

Leonard Apeltsin

October 2021
ISBN 9781617296253
704 pages

Included with a Manning Online subscription

printed in black & white

Available translations: Complex Chinese, Korean, Russian, Simplified Chinese

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Learn data science with Python by 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.

about the technology

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.

about the book

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

about the reader

For readers who know the basics of Python. No prior data science or machine learning skills required.

about the author

Leonard Apeltsin is the Head of Data Science at Anomaly, where his team applies advanced analytics to uncover healthcare fraud, waste, and abuse.

eBook

$47.99 $33.59

include audio $24.99 $17.49

Valuable and accessible… a solid foundation for anyone aspiring to be a data scientist.

Amaresh Rajasekharan, IBM Corporation

Really good introduction of statistical data science concepts. A must-have for every beginner!

Simone Sguazza, University of Applied Sciences and Arts of Southern Switzerland

A full-fledged tutorial in data science including common Python libraries and language tricks!

Jean-François Morin, Laval University

This book is a complete package for understanding how the data science process works end to end.

Ayon Roy, Internshala

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