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This Week in Data Science (March 21, 2017)

Posted on October 08, 2020 by Jacky Tea

This Week in Data Science (March 21, 2017)

Posted on March 21, 2017 by Janice Darling

Here’s this week’s news in Data Science and Big Data.hybrid-cloud

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INTERESTING DATA SCIENCE ARTICLES AND NEWS

  • Interactive or not to interactive visualization?
    – Things to keep in mind when tailoring visualization to different audiences.
  • Applying Machine Learning To March Madness
    – Can Machine Learning tackle March Madness Predictions?
  • 4 Tricks for working with R, Leaflet and Shiny – Four tricks to consider to improve apps.
  • 17 More Must-Know Data Science Interview Questions and Answers, Part 3
    – Sample Data Science interview questions covering topics such as A/B testing, data visualization among other topics.
  • If You Care About Bid Data, You Care About Stream Processing – How stream processing is used to manage large volumes of data.
  • Visualization choice depends on the data and the questions
    – Factors that affect the dataset and visualization choice in Data Visualization projects.
  • 7 Types of Data Scientist Job Profiles
    – A condensed description of 7 different Data Scientist profiles.
  • Understanding the power of real-time geospatial analytics
    – The uses of geospatial analytics in monitoring IoT devices.
  • 6 Business Concepts you need to become a Data Science Unicorn
    – 6 concepts Data Scientists should know in order to solve data science problems from a business point of view.
  • A vision of hybrid cloud for big data and analytics
    – A definition and outlook of the Hybrid Cloud for Big Data and Analytics.
  • Neural Networks: How they work, and how to train them in R
    – An overview of Neural Networks and dedicated packages in R.
  • Text Analytics: A Primer
    – A brief discussion about the History and uses of Text Analytics.
  • List of Must- Read Free Books for Data Science
    – A list of recommended books to read for Data Science.
  • So You Built a Machine Learning Model?
    – Tips for improving Machine Learning Models.
  • IBM’s Watson Is Tackling Healthcare With Artificial Intelligence
    – How Watson’s ability to analyze large amounts of data make it a natural fit for medical applications.

FEATURED COURSES FROM BDU

  • Big Data 101 – What Is Big Data? Take Our Free Big Data Course to Find Out.
  • Predictive Modeling Fundamentals I
    – Take this free course and learn the different mathematical algorithms used to detect patterns hidden in data.
  • Using R with Databases
    – Learn how to unleash the power of R when working with relational databases in our newest free course.
  • Deep Learning with TensorFlow – Take this free TensorFlow course and learn how to use Google’s library to apply deep learning to different data types in order to solve real world problems.

COOL DATA SCIENCE VIDEOS

  • Machine Learning With Python – Supervised VS Unsupervised Learning
    –The basics of Supervised and Unsupervised Learning.
  • Machine Learning With Python – Supervised Learning Classification
    – An overview of classification.
  • Machine Learning With Python – Unsupervised Learning
    – An overview and real world applications of Unsupervised Learning.

Tags: analytics, Big Data, data science, weekly roundup

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