Book Name: Practical Data Analysis
Category: Machine Learning
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Practical Data Analysis by Hector Cuesta, Sampath Kumar

Many small businesses are faced with large amounts of data, but lack the in-house skills to perform quantitative analysis. Understanding how harnessing the power of data analytics with the latest open source technology can help them deliver better customer service, visualize customer needs, or even gain new insights into performance. performance of previous products. Real Data Analytics is an ideal book for individuals and small businesses who want to slice and dice the data they have without much hassle.

Realistic data analysis is a practical guide to understanding the nature of your data and turning it into insights. He’ll show you how to use machine learning techniques, social media analytics, and econometrics to help your clients better understand the data sources they have. Data preparation and processing on several types of data such as text, images, graphics, documents and time series will also be covered.

Table of Contents

  1. Getting Started
  2. Preprocessing 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 Diseases with Cellular Automata
  10. Working with Social Graphs
  11. Working with Twitter Data
  12. Data Processing and Aggregation with MongoDB
  13. Working with MapReduce
  14. Online Data Analysis with Jupyter and Wakari
  15. Understanding Data Processing using Apache Spark

Practical Data Analysis by Hector Cuesta, Sampath Kumar Free PDF

About the Author

Hector Cuesta is founder and Chief Data Scientist at Dataxios, a machine intelligence research company. Holds a BA in Informatics and a M.Sc. in Computer Science. He provides consulting services for data-driven product design with experience in a variety of industries including financial services, retail, fintech, e-learning and Human Resources. He is an enthusiast of Robotics in his spare time.

Dr. Sampath Kumar works as an assistant professor and head of Department of Applied Statistics at Telangana University. He has completed M.Sc., M.Phl., and Ph. D. in statistics. He has five years of teaching experience for PG course. He has more than four years of experience in the corporate sector. His expertise is in statistical data analysis using SPSS, SAS, R, Minitab, MATLAB, and so on. He is an advanced programmer in SAS and matlab software. He has teaching experience in different, applied and pure statistics subjects such as forecasting models, applied regression analysis, multivariate data analysis, operations research, and so on for M.Sc. students. He is currently supervising Ph.D. scholars.

Key Features

  • 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

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

 

Practical Data Analysis PDF

Author(s): Hector Cuesta, Sampath Kumar

Publisher: Packt Publishing, Year: 2016

ISBN: 1785289713,9781785289712

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