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References and Acknowledgements

Discover a curated list of important documentation, tutorials, articles, and books on data science and machine learning. This lesson guides you to valuable resources that support your learning and application of core concepts, models, and techniques.

We'll cover the following...

Acknowledgements:

  • Numpy Documentation


  • Scikit Learn Documentation


  • TensorFlow Documentation


  • Open GPU Data Science (RAPIDS)


  • MapReduce Tutorial – Fundamentals of MapReduce with MapReduce Example (Edureka)


  • Sampling Techniques by Seema Singh (Towards Data Science)


  • Amazon Whitepapers


  • Data Mining: Concepts and Techniques by Jiawei Han Micheline Kamber Jian Pei


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