Data science is a discipline at the intersection of machine learning, statistics, and data mining with the objective of gaining new knowledge from existing data by means of algorithmic and statistical analysis. In this book, you will learn the seven most important ways in data science of analyzing 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 your knowledge of a particular type of analysis.
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Book Overview & Buying
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Table Of Contents
Data Science Algorithms in a Week - Second Edition
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Data Science Algorithms in a Week
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Overview of this book
Machine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data. To address the complex nature of various real-world data problems, specialized machine learning algorithms have been developed. Through algorithmic and statistical analysis, these models can be leveraged to gain new knowledge from existing data as well.
Data Science Algorithms in a Week addresses all problems related to accurate and efficient data classification and prediction. Over the course of seven days, you will be introduced to seven algorithms, along with exercises that will help you understand different aspects of machine learning. You will see how to pre-cluster your data to optimize and classify it for large datasets. This book also guides you in predicting data based on existing trends in your dataset. This book covers algorithms such as k-nearest neighbors, Naive Bayes, decision trees, random forest, k-means, regression, and time-series analysis.
By the end of this book, you will understand how to choose machine learning algorithms for clustering, classification, and regression and know which is best suited for your problem
Table of Contents (12 chapters)
Preface
Free Chapter
Classification Using K-Nearest Neighbors
Naive Bayes
Decision Trees
Random Forests
Clustering into K Clusters
Regression
Time Series Analysis
Python Reference
Glossary of Algorithms and Methods in Data Science
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