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By Hector Cuesta

Key Features

  • Learn to exploit quite a few information research instruments and algorithms to categorise, cluster, visualize, simulate, and forecast your data
  • Apply computing device studying algorithms to other kinds of knowledge akin to social networks, time sequence, and images
  • A hands-on consultant to realizing the character of information and the way to show it into insight

Book Description

Beyond buzzwords like significant info or information technological know-how, there are an outstanding possibilities to innovate in lots of companies utilizing information research to get data-driven items. info research consists of asking many questions about information so one can become aware of insights and generate price for a product or a service.

This booklet explains the elemental facts algorithms with no the theoretical jargon, and you will get hands-on turning information into insights utilizing computing device studying concepts. we'll practice data-driven innovation processing for different types of information comparable to textual content, pictures, social community graphs, records, and time sequence, displaying you the way to enforce huge facts processing with MongoDB and Apache Spark.

What you'll learn

  • Acquire, structure, and visualize your data
  • Build an image-similarity seek engine
  • Generate significant visualizations an individual can understand
  • Get all started with reading social community graphs
  • Find out tips on how to enforce sentiment textual content analysis
  • Install info research instruments corresponding to Pandas, MongoDB, and Apache Spark
  • Get to grips with Apache Spark
  • Implement computing device studying algorithms akin to class or forecasting

About the Author

Hector Cuesta is founder and leader facts Scientist at Dataxios, a computer intelligence examine corporation. Holds a BA in Informatics and a M.Sc. in machine technological know-how. He offers consulting companies for data-driven product layout with event in a number of industries together with monetary prone, retail, fintech, e-learning and Human assets. he's an fanatic of Robotics in his spare time.

Dr. Sampath Kumar works as an assistant professor and head of division of utilized data at Telangana collage. He has accomplished M.Sc., M.Phl., and Ph. D. in information. He has 5 years of training event for PG direction. He has greater than 4 years of expertise within the company area. His services is in statistical info research utilizing SPSS, SAS, R, Minitab, MATLAB, etc. he's a complicated programmer in SAS and matlab software program. He has instructing event in several, utilized and natural facts matters akin to forecasting versions, utilized regression research, multivariate info research, operations study, and so forth for M.Sc. scholars. he's at present supervising Ph.D. scholars.

Table of Contents

  1. Getting Started
  2. Preprocessing Data
  3. Getting to Grips with Visualization
  4. Text Classification
  5. Similarity-Based picture Retrieval
  6. Simulation of inventory Prices
  7. Predicting Gold Prices
  8. Working with aid Vector Machines
  9. Modeling Infectious ailments with mobile Automata
  10. Working with Social Graphs
  11. Working with Twitter Data
  12. Data Processing and Aggregation with MongoDB
  13. Working with MapReduce
  14. Online information research with Jupyter and Wakari
  15. Understanding facts Processing utilizing Apache Spark

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About the Reviewers Chandana N. Athauda is currently employed at BAG (Brunei Accenture Group) Networks—Brunei and he serves as a technical consultant. He mainly focuses on Business Intelligence, Big Data and Data Visualization tools and technologies. He has been working professionally in the IT industry for more than 15 years (Ex-Microsoft Most Valuable Professional (MVP) and Microsoft Ranger for TFS). His roles in the IT industry have spanned the entire spectrum from programmer to technical consultant.

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Python is a "scripting language" - an interpreted language with its own built-in memory management and good facilities for calling and co-operating with other programs. x version, because this is under active development and has already seen over two years of stable releases. NET virtual machines. Python has powerful standard libs and a wealth of third-party packages for numerical computation and machine learning, such as NumPy, SciPy, pandas, SciKit, mlpy, and so on. Python is excellent for beginners, yet great for experts, is highly scalable, and is also suitable for large projects as well as small ones.

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