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Write fast, space-efficient, and scalable code using the easy-to-understand algorithms and data structures in this book.
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With Grokking Statistics, you’ll build a strong foundation in statistical analysis by working through engaging mini projects that put eac...
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We’re supporting Starlight, which helps entertain and distract scared and lonely kids. Please give what you can (even if you already own ...
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Privacy Preserving Machine Learning is a practical guide to keeping ML data anonymous and secure. You’ll learn the core principles behind...
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Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of techniques for evaluating new features and fine-...
New
If you are making your own formats of YAML files, you may like the article that we wrote showing how to make Visual Studio Code and a few...
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The world is experiencing a data revolution, led by AI. However, only 48% of AI projects reach production, taking an average of 8.2 month...
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SQL Antipatterns is a short-cut to wisdom, showing you how to avoid "easy" solutions that don't work, and be a better database developer ...
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Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for t...
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Battle cost overruns, death marches, and legacy code monsters with novel ways to identify and prioritize technical debt, based on behavio...
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Each chapter in this book helps you identify, explain, and correct a unique and dangerous antipattern. The four parts of the book group t...
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Data Mesh in Action reveals how this groundbreaking architecture looks for both small startups and large enterprises. You’ll see a data m...
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How to Lead in Data Science teaches strategies for thriving in data leadership and advancing your career in this competitive field. In th...
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Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee.
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Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learnin...
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In episode 104 of Thinking Elixir, Chris Grainger explains Explorer, Nx’s recent addition. It’s a “Data Frame” library which sounds far m...
New
In episode 102 of Thinking Elixir, Sean Moriarity, the author of Genetic Algorithms in Elixir, lays out Machine Learning in the Elixir sp...
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Learn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, a...
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