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Nishant Shukla

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    Machine Learning with Tensorflow
    Haskell Data Analysis Cookbook
    • Haskell Data Analysis Cookbook

      • 334pages
      • 12 heures de lecture
      3,9(17)Évaluer

      Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes. This book will take you on a voyage through all the steps involved in data analysis. It provides synergy between Haskell and data modeling, consisting of carefully chosen examples featuring some of the most popular machine learning techniques. You will begin with how to obtain and clean data from various sources. You will then learn how to use various data structures such as trees and graphs. The meat of data analysis occurs in the topics involving statistical techniques, parallelism, concurrency, and machine learning algorithms, along with various examples of visualizing and exporting results. By the end of the book, you will be empowered with techniques to maximize your potential when using Haskell for data analysis.

      Haskell Data Analysis Cookbook
    • Machine Learning with Tensorflow

      • 272pages
      • 10 heures de lecture

      The book highlights essential features that enhance understanding and engagement with the content. It provides clear explanations, practical examples, and interactive elements designed to facilitate learning. Each section is structured to promote critical thinking and application of concepts, making it suitable for a variety of readers. The focus on key features ensures a comprehensive grasp of the subject matter, catering to both novices and those seeking to deepen their knowledge.

      Machine Learning with Tensorflow