Practical Data Analysis (Python, MongoDB, Apache Spark) (pdf)

Description

Book Description

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

About the Author

Hector Cuesta co-founded and is a data-driven product designer at DataNerdsMX, a data science consulting firm in Mexico City. He holds an MSc in Computer Science. He provides consulting services for software engineering and data science and has 10+ years of experience in a variety of industries including financial services, social networking, e-learning, and Human Resources. He is an enthusiast of Lego Robotics and Raspberry Pi and pursues these topics in his spare time.