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Hands-On Data Analysis with Pandas - Second Edition

You're reading from  Hands-On Data Analysis with Pandas - Second Edition

Product type Book
Published in Apr 2021
Publisher Packt
ISBN-13 9781800563452
Pages 788 pages
Edition 2nd Edition
Languages
Concepts
Author (1):
Stefanie Molin Stefanie Molin
Profile icon Stefanie Molin

Table of Contents (21) Chapters

Preface Section 1: Getting Started with Pandas
Chapter 1: Introduction to Data Analysis Chapter 2: Working with Pandas DataFrames Section 2: Using Pandas for Data Analysis
Chapter 3: Data Wrangling with Pandas Chapter 4: Aggregating Pandas DataFrames Chapter 5: Visualizing Data with Pandas and Matplotlib Chapter 6: Plotting with Seaborn and Customization Techniques Section 3: Applications – Real-World Analyses Using Pandas
Chapter 7: Financial Analysis – Bitcoin and the Stock Market Chapter 8: Rule-Based Anomaly Detection Section 4: Introduction to Machine Learning with Scikit-Learn
Chapter 9: Getting Started with Machine Learning in Python Chapter 10: Making Better Predictions – Optimizing Models Chapter 11: Machine Learning Anomaly Detection Section 5: Additional Resources
Chapter 12: The Road Ahead Solutions
Other Books You May Enjoy Appendix

Practicing working with data

Throughout this book, we have worked with various datasets from different sources with step-by-step instructions. It doesn't have to stop here, though. This section is dedicated to some resources that can be used to continue with guided instruction and, eventually, work toward building a model for a predefined problem.

Kaggle (https://www.kaggle.com/) offers content for learning data science, datasets for exploration that are shared by members of the community, and competitions that have been posted by companies—perhaps the Netflix recommendation contest sounds familiar (https://www.kaggle.com/netflix-inc/netflix-prize-data)? These contests are a great way for you to practice your machine learning skills and become more visible in the community (especially to potential employers).

Important note

Kaggle isn't the only place you can participate in data science competitions. Some additional ones are listed at https://towardsdatascience...

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