You might already know that there's a wealth of data science and machine learning resources available on the market, but what you might not know is how much is left out by most of these AI resources. This book not only covers everything you need to know about algorithm families but also ensures that you become an expert in everything, from the critical aspects of avoiding bias in data to model interpretability, which have now become must-have skills.

In this book, you'll learn how using Anaconda as the easy button, can give you a complete view of the capabilities of tools such as conda, which includes how to specify new channels to pull in any package you want as well as discovering new open source tools at your disposal. You'll also get a clear picture of how to evaluate which model to train and identify when they have become unusable due to drift. Finally, you'll learn about the powerful yet simple techniques that you can use to explain how your model works.

By the end of this book, you'll feel confident using conda and Anaconda Navigator to manage dependencies and gain a thorough understanding of the end-to-end data science workflow.

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Spis treści

Building Data Science Solutions with Anaconda. A comprehensive starter guide to building robust and complete models eBook -- spis treści

• 1. Understanding the AI/ML Landscape
• 2. Analyzing Open Source Software
• 3. Using Anaconda Distribution to Manage Packages
• 4. Working with Jupyter Notebooks and NumPy
• 5. Cleaning and Visualizing Data
• 6. Overcoming Bias in AI/ML
• 7. Choosing the Best AI Algorithm
• 8. Dealing with Common Data Problems
• 9. Building a Regression Model with scikit-learn
• 10. Explainable AI - Using LIME and SHAP
• 11. Tuning Hyperparameters and Versioning Your Model