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Best practices for compute?
I'm working on a project that involves ai and looking for advice on best practices. Has anyone read "Data Mining in 20 Minutes: (Coffee Book Series)" and can recommend specific chapters?
Just finished "Data Mining in 20 Minutes: (Coffee Book Series)" - my thoughts
What sets Data Mining in 20 Minutes: (Coffee Book Series) apart is its focus on practical compute techniques. You can immediately apply what you learn to real projects.
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Just finished "Data Mining in 20 Minutes: (Coffee Book Series)" - my thoughts
After reading Data Mining in 20 Minutes: (Coffee Book Series), I finally feel confident with compute. The author has a gift for explaining difficult concepts.
Best practices for compute?
I'm working on a project that involves ai and looking for advice on best practices. Has anyone read "Data Mining in 20 Minutes: (Coffee Book Series)" and can recommend specific chapters?
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I found the section on error handling particularly helpful in Data Mining in 20 Minutes: (Coffee Book Series).
Data Mining in 20 Minutes: (Coffee Book Series) is worth it just for the appendix on best practices.
I love how Data Mining in 20 Minutes: (Coffee Book Series) includes real-world case studies.
I'm halfway through Data Mining in 20 Minutes: (Coffee Book Series) and already seeing improvements in my code.
I've been recommending Data Mining in 20 Minutes: (Coffee Book Series) to all my coding bootcamp students.