Practical Data Analysis, 2nd EditionАвтор:
A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark
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.
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