A practical guide to obtaining, transforming, exploring, and
analyzing data using Python, MongoDB, and Apache Spark About This
Book * Learn to use various data analysis tools and algorithms to
classify, cluster, visualize, simulate, and forecast your data *
Apply Machine Learning algorithms to different kinds of data such
as social networks, time series, and images * A hands-on guide to
understanding the nature of data and how to turn it into insight
Who This Book Is For This book is for developers who want to
implement data analysis and data-driven algorithms in a practical
way. It is also suitable for those without a background in data
analysis or data processing. Basic knowledge of Python programming,
statistics, and linear algebra is assumed. What You Will Learn *
Acquire, format, and visualize your data * Build an
image-similarity search engine * Generate meaningful visualizations
anyone can understand * Get started with analyzing social network
graphs * Find out how to implement sentiment text analysis *
Install data analysis tools such as Pandas, MongoDB, and Apache
Spark * Get to grips with Apache Spark * Implement machine learning
algorithms such as classification or forecasting In Detail Beyond
buzzwords like Big Data or Data Science, there are a great
opportunities to innovate in many businesses using data analysis to
get data-driven products. Data analysis involves asking many
questions about data in order to discover insights and generate
value for a product or a service. This book explains the basic data
algorithms without the theoretical jargon, and you'll get hands-on
turning data into insights using machine learning techniques. We
will perform data-driven innovation processing for several types of
data such as text, Images, social network graphs, documents, and
time series, showing you how to implement large data processing
with MongoDB and Apache Spark. Style and approach This is a
hands-on guide to data analysis and data processing. The concrete
examples are explained with simple code and accessible data.
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