Machine Learning Algorithms for Data Scientists An Overview Book [PDF] Download

Download the fantastic book titled Machine Learning Algorithms for Data Scientists An Overview written by Vinaitheerthan Renganathan, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Machine Learning Algorithms for Data Scientists An Overview", which was released on 02 June 2021. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Machine Learning Algorithms for Data Scientists An Overview by Vinaitheerthan Renganathan PDF

Machine Learning models are widely used in different fields such as Artificial Intelligence, Business, Clinical and Biological Sciences which includes self-driving cars, predictive models, disease prediction, genome sequencing, spam filtering, product recommendation, fraud detection and image recognition . It has gained importance due to its capabilities of handling large volume of data, prediction and classification accuracy and validation procedures. Machine Learning models are built on the basis of statistical and mathematical algorithms. One important aspect of machine learning is it does not stick to standard algorithm throughout modeling process instead it learns from the data over a period of time and improves the accuracy of the model. Classification and prediction tasks are carried out based on the characteristics, patterns and relationship of the features present in the data set. Machine learning model also forms the basis of Deep Learning models. Machine Learning models involve supervised learning, unsupervised learning, semi supervised learning and reinforcement learning algorithms. Data Scientists analyze, model and visualize data and provide actionable insights to the decision makers. Machine learning algorithms and tools help the data scientist to carry out these tasks with the help of software such R and Python. This book provides an overview of Machine Learning models, algorithms and its application in different fields through the use of R Software. It also provides short introduction to R software for the benefit of users. Author assumes the users have basic descriptive and inferential statistical knowledge which is essential for building Machine Learning models. Data sets used in the books can be downloaded from the author’s website.


Detail About Machine Learning Algorithms for Data Scientists An Overview PDF

  • Author : Vinaitheerthan Renganathan
  • Publisher : Vinaitheerthan Renganathan
  • Genre : Computers
  • Total Pages : 102 pages
  • ISBN : 9354737692
  • PDF File Size : 47,6 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Machine Learning Algorithms for Data Scientists: An Overview

Machine Learning Algorithms for Data Scientists: An Overview
  • Publisher : Vinaitheerthan Renganathan
  • File Size : 31,8 Mb
  • Release Date : 02 June 2021
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Machine Learning models are widely used in different fields such as Artificial Intelligence, Business, Clinical and Biological Sciences which includes self-driving cars, predictive models, disease prediction, genome sequencing, spam filtering,

Data Science and Machine Learning

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  • Release Date : 20 November 2019
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Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

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  • Publisher : BoD – Books on Demand
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  • Release Date : 24 July 2017
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Build strong foundation for entering the world of Machine Learning and data science with the help of this comprehensive guide About This Book Get started in the field of Machine

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  • Publisher : CRC Press
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  • Release Date : 20 November 2019
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Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical

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  • Publisher : "O'Reilly Media, Inc."
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Many Python developers are curious about what machine learning is and how it can be concretely applied to solve issues faced in businesses handling medium to large amount of data.

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  • Publisher : Unknown Publisher
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******Free eBook for customers who purchase the print book from Amazon****** Are you thinking of learning data science with easiest way (For Beginners)? If you are looking for a complete

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  • Publisher : Cambridge University Press
  • File Size : 52,9 Mb
  • Release Date : 20 September 2012
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Covering all the main approaches in state-of-the-art machine learning research, this will set a new standard as an introductory textbook.

Advances in Machine Learning and Data Science

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  • Publisher : Springer
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The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and

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  • Publisher : Packt Publishing Ltd
  • File Size : 55,7 Mb
  • Release Date : 31 October 2018
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Build a strong foundation of machine learning algorithms in 7 days Key FeaturesUse Python and its wide array of machine learning libraries to build predictive models Learn the basics of the 7