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Building Data Science Solutions with Anaconda

You're reading from  Building Data Science Solutions with Anaconda

Product type Book
Published in May 2022
Publisher Packt
ISBN-13 9781800568785
Pages 330 pages
Edition 1st Edition
Languages
Author (1):
Dan Meador Dan Meador
Profile icon Dan Meador

Table of Contents (16) Chapters

Preface 1. Part 1: The Data Science Landscape – Open Source to the Rescue
2. Chapter 1: Understanding the AI/ML landscape 3. Chapter 2: Analyzing Open Source Software 4. Chapter 3: Using the Anaconda Distribution to Manage Packages 5. Chapter 4: Working with Jupyter Notebooks and NumPy 6. Part 2: Data Is the New Oil, Models Are the New Refineries
7. Chapter 5: Cleaning and Visualizing Data 8. Chapter 6: Overcoming Bias in AI/ML 9. Chapter 7: Choosing the Best AI Algorithm 10. Chapter 8: Dealing with Common Data Problems 11. Part 3: Practical Examples and Applications
12. Chapter 9: Building a Regression Model with scikit-learn 13. Chapter 10: Explainable AI - Using LIME and SHAP 14. Chapter 11: Tuning Hyperparameters and Versioning Your Model 15. Other Books You May Enjoy

To get the most out of this book

All the software used in this book is open source, meaning you will not have to pay for any of it. If you do find it useful, you are encouraged to find ways to give back to these communities, either financially or by contributing to the code base directly. NumFOCUS sponsors many of the tools used; you can find more about them at their website: https://numfocus.org/.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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