Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you’ll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas.
With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you’ll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You’ll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means.

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Spis treści

Principles of Data Science. Mathematical techniques and theory to succeed in data-driven industries eBook -- spis treści

• 1. How to Sound like a Data Scientist
• 2. Types of Data
• 3. The Five Steps of Data Science
• 4. Mathematics -- The Basics
• 5. Impossible or Improbable? – An Introduction to Probability
• 6. Advanced Probability
• 7. What are the Chances? – An Introduction to Statistics
• 8. Advanced Statistics
• 9. Say What? -- Communicating Data
• 10. How to tell if your toaster is learning -- Machine Learning Essentials
• 11. Predictions Don’t Grow on Trees, or do they? -- Beyond Statistical Modelling
• 12. Beyond the Essentials
• 13. Case Studies