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 Title: Data Science Algorithms in a Week: Top 7 Algorithms for Computing, Data Analysis, and Machine Learning
 Author(s) David Natingga
 Publisher: Packt Publishing (August 16, 2017)
 Paperback: 210 pages
 eBook: PDF
 Language: English
 ISBN10/ASIN: 1787284581
 ISBN13: 9781787284586
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Book Description
This book will address the problems related to accurate and efficient data classification and prediction. Over the course of 7 days, you will be introduced to seven algorithms, along with exercises that will help you learn different aspects of machine learning. You will see how to precluster your data to optimize and classify it for large datasets. You will then find out how to predict data based on the existing trends in your datasets.
It covers algorithms such as: kNearest Neighbors, Naive Bayes, Decision Trees, Random Forest, kMeans, Regression, and Timeseries. On completion of the book, you will understand which machine learning algorithm to pick for clustering, classification, or regression and which is best suited for your problem.
 Find out how to classify using Naive Bayes, Decision Trees, and Random Forest to achieve accuracy to solve complex problems
 Identify a data science problem correctly and devise an appropriate prediction solution using Regression and Timeseries
 See how to cluster data using the kMeans algorithm
 Get to know how to implement the algorithms efficiently in the Python and R languages
 David Natingga is a mathematician and theoretical computer scientist of a Slovak descent working on the mathematics of a mind.
 Data Science
 Algorithms and Data Structures
 Data Analysis and Data Mining, Big Data
 Machine Learning
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