This Week in Data Science (February 28, 2017)

Posted on February 28, 2017 by Janice Darling

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

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INTERESTING DATA SCIENCE ARTICLES AND NEWS

• http://www.ibmbigdatahub.com/blog/four-perspectives-data-lakes – The relation of architecture, value, innovation and governance to data lakes.
• Fueling the Gold Rush: The Greatest Public Datasets for AI – A run down of some public datasets for Artificial Intelligence.
• Pandas Cheat Sheet – Python for Data Science – Cheat sheet for one of the most popular data science packages.
• 17 More Must-Know Data Science Interview Questions and Answers, Part 2 – Additional must-know questions for data science interviews.
• IBM, Northern Trust partner on financial security blockchain tech – IBM and Northern Trust partner to develop blockchain technology for the management of private equity funds and services.
• The Origins of Big Data – A perspective summary of the field and use of the term Big Data.
• How is Deep Learning Changing Data Science Paradigms? – A look at the rise of Deep Learning and its effect on Data Science Paradigms.
• Melbourne IBM Research team using Watson AI to identify glaucoma – Melbourne-based IBM research team trains Watson to identify eye abnormalities.
• Removing Outliers Using Standard Deviation in Python – How to remove outliers using a well known but underutilized metric.
• R Packages worth a look – A short list and summaries of R statistical and graphical packages.
• 25 Big Data Terms Everyone Should Know – Big Data Terms and concepts as an introduction to the field.
• Moving from R to Python: The Libraries You Need to Know – Python packages and their R contemporaries.
• Predicting the 2017 Oscar Winners – Using Machine Learning to predict the winners at the 89th annual Academy of Motion Picture Arts and Sciences Awards.
• How To Hire A Data Scientist: 5 Don’ts For Data Scientist Interview Questions – How hiring managers can land a proficient data scientist.
• Artificial intelligence: Understanding how machines learn – The current limits of Artificial Intelligence and Machine Learning.

UPCOMING DATA SCIENCE EVENTS

• IBM Webinar: Are you getting enough value from your relational database? – March 1, 2017 @ 1:00 pm – 2:00 pm
• IBM Webinar: Art of the Possible…and the Reality of Execution – March 2, 2017 @ 1:00 pm – 2:00 pm

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.

COOL DATA SCIENCE VIDEOS

• Deep Learning with TensorFlow Course Summary – A summary of our free course here at BDU Deep Learning with TensorFlow.
• Deep Learning with Tensorflow – Deep Belief Networks
  – An overview of Deep Belief Networks.
• Deep Learning with Tensorflow – Autoencoder Structure
  –An overview of the structure and applications of an Autoencoder.
• Deep Learning with Tensorflow – Autoencoders with TensorFlow
  –Tutorial on how to implement an Autoencoder using TensorFlow.
• Deep Learning with Tensorflow – Introduction to Autoencoders
  – The basic concepts of Autoencoders – a type of neural network.

Tags: analytics, Big Data, data science