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.

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Spis treści

Practical Data Analysis. Pandas, MongoDB, Apache Spark, and more - Second Edition eBook -- spis treści

• 1. Getting Started with Data Analysis
• 2. Preprocessing the Data
• 3. Getting to Grips with Visualization
• 4. Text Classification
• 5. Similarity-based Image Retrieval
• 6. Simulation of Stock Prices
• 7. Predicting Gold Prices
• 8. Working with Support Vector Machines
• 9. Modeling Infectious Disease with Cellular Automata
• 10. Visualizing Social Network Graphs
• 11. Sentiment Analysis of Twitter Data
• 12. Data Processing and Aggregation with MongoDB
• 13. Working with MapReduce
• 14. On-line Data Analysis with Jupyter and Wakari
• 15. Big Data Using Spark