Data science is a discipline at the intersection of machine learning, statistics and data mining with the objective to gain new knowledge from the existing data by the means of algorithmic and statistical analysis. In this book you will learn the 7 most important ways in Data Science to analyze the data. Each chapter first explains its algorithm or analysis as a simple concept supported by a trivial example. Further examples and exercises are used to build and expand the knowledge of a particular analysis.
Data Science Algorithms in a Week
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Data Science Algorithms in a Week
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Overview of this book
<p>Machine learning applications are highly automated and self-modifying, and they continue to improve over time with minimal human intervention as they learn with more data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed that solve these problems perfectly. Data science helps you gain new knowledge from existing data through algorithmic and statistical analysis.</p>
<p>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 pre-cluster 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.</p>
<p>This book covers algorithms such as: k-Nearest Neighbors, Naive Bayes, Decision Trees, Random Forest, k-Means, Regression, and Time-series. 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.</p>
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Data Science Algorithms in a Week
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Table of Contents (12 chapters)
Preface
Free Chapter
Classification Using K Nearest Neighbors
Naive Bayes
Decision Trees
Random Forest
Clustering into K Clusters
Regression
Time Series Analysis
R Reference
Python Reference
Glossary of Algorithms and Methods in Data Science
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