Machine Learning Top 10 Articles for the Past Month

Machine Learning Top 10 Articles for the Past Month.

  • Machine Learning Top 10 Articles for the Past MonthFor the past month (March, 2017), we’ve ranked nearly 1,300 Machine Learning articles to pick the Top 10 stories that can help advance your career.Topics included in this React list are: NLP, Neural Networks, Deep Learning, A.I.,TensorFlow, Keras, Text-To-Speech, Algorithms.
  • The lists for Python are published separately in the publication.Mybridge AI ranks articles based on the quality of content measured by our machine and a variety of human factors including engagement and popularity.
  • This is a competitive list (0.77% chance to be included) and you’ll find the experience and techniques shared by the leading Data Scientists useful.

For the past month (March, 2017), we’ve ranked nearly 1,300 Machine Learning articles to pick the Top 10 stories that can help advance your career.
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Hugo Larochelle’s neural network & deep learning tutorial videos, subtitled & screengrabbed ~ prooffreader plus

.@hugo_larochelle #NeuralNetwork & #DeepLearning tutorial videos, subtitled & screengrabbed

  • Like a lot of data scientists (I consider myself more of a data spelunker, but I aspire to data science), I try my best to keep up with the latest discoveries in a very fast-changing field; and probably nothing has been as game-changing as the advent of deep learning.
  • used youtube-dl to download the videos and WEBVTT subtitles;
  • Doing data science, I often start loop functions without a clear idea of how long they’ll take.
  • used ffmpeg (from a subprocess call) to add a black letterbox below each video, burn the subtitles into that box and then save png screenshots wherever there was a new subtitle line;
  • Deep Learning, explained to a five-year-old (okay, maybe fifteen-year-old): Data science been really good for a while now at data that can be explained in Excel spreadsheets, i.e. columns and rows: one row per observation, one column per variable.

By David Taylor10:22 AMdeep.learning, learning, machine.learning, neural.networks, pdfs, tutorial, videos4 comments

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Machine Learning Moves the Needle on Neural Science

Find out which data scientists won the first Decoding Brain Signals competition

  • Data Scientists Decode Human Perceptions from Brain Signals
  • When we can read and decode brain signals, we can help treat, heal, and retrain a brain after injury.”
  • Being able to decode human perceptions from brain signals can benefit this population greatly.
  • To learn more about upcoming competitions, click on this link or the image below: Cortana Intelligence Competitions .
  • Machine Learning Moves the Needle on Neural Science

Millions of people suffer from brain-related injuries and disorders every year. Being able to decode human perceptions from brain signals can benefit this population greatly. That’s what inspired Stanford University neurosurgeon Dr. Kai Miller to team up with Microsoft to offer the inaugural Cortana Intelligence Competition: Decoding Brain Signals. 

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Register Now for the First Microsoft Data Science Summit

More info on the Microsoft #DataScience Summit:  - register today #MachineLearning #BigData

  • Click to register for the Microsoft Data Science Summit .
  • I am super excited about the very first Microsoft Data Science Summit , to be held in Atlanta on September 26-27, 2016, and invite all data scientists, big data engineers and machine learning practitioners among you to attend.
  • You will also have an opportunity to network with other data scientists and software engineers .
  • Posted by Joseph Sirosh, Corporate Vice President of the Data Group at Microsoft.
  • How to handle Real-Time and Streaming Data .

Read the full article, click here.


@josephsirosh: “More info on the Microsoft #DataScience Summit: – register today #MachineLearning #BigData”


I am super excited about the very first Microsoft Data Science Summit, to be held in Atlanta on September 26-27, 2016, and invite all data scientists, big data engineers and machine learning practitioners among you to attend.


Register Now for the First Microsoft Data Science Summit

Building a Data Science Portfolio: Machine Learning Project Part 1

Building a #DataScience Portfolio: Machine Learning Project Part 1  @dataquestio

  • KDnuggets Home > News > 2016 > Jul > Tutorials, Overviews > Building a Data Science Portfolio: Machine Learning Project Part 1 ( 16:n27 )
  • Dataquest’s founder has put together a fantastic resource on building a data science portfolio.
  • A loan that is acquired may have dozens of rows in the performance data.
  • A good way to think of this is that the acquisition data tells you that Fannie Mae now controls the loan, and the performance data contains a series of status updates on the loan.
  • A good dataset for an end to end portfolio project can be hard to find.

Read the full article, click here.


@kdnuggets: “Building a #DataScience Portfolio: Machine Learning Project Part 1 @dataquestio”


Dataquest’s founder has put together a fantastic resource on building a data science portfolio. This first of three parts lays the groundwork, with subsequent posts over the following 2 days. Very comprehensive!


Building a Data Science Portfolio: Machine Learning Project Part 1

Demystifying Machine Learning Part 4: Image and Video Applications

Demystifying #MachineLearning Part 4: Image and Video Applications from @AnandSRao:  #AI

  • Deep learning requires large volumes of data in order for a system to learn the features and should not be attempted where data is sparse.
  • , deep learning is suitable only for certain classes of problems and cannot be seen as a panacea to solve all problems.
  • In the previous post in our Machine Learning series, we dived into the inner workings of deep learning .
  • Previous post: Sportifying STEM through Robotics to Stimulate Learning
  • Demystifying Machine Learning Part 4: Image and Video Applications

Read the full article, click here.


@PwCAdvisory: “Demystifying #MachineLearning Part 4: Image and Video Applications from @AnandSRao: #AI”


How are companies using deep learning to drive business goals? Improved image and video recognition, audio recognition, and language understanding.


Demystifying Machine Learning Part 4: Image and Video Applications

What Data Scientists Do All Day at Work

What do #DataScientists do all day at work?  #BigData #DataScience #MachineLearning

  • What Data Scientists Do All Day at Work
  • Demand for data scientists is growing, driven by companies and government agencies that are flooded with data and struggling to make sense of it.
  • Tesla Has No Plans to Disable Autopilot Feature in Its Cars
  • Starbucks Raises Prices on Some Drinks
  • Santander’s U.K. Cash Cow Is Put at Risk by Brexit

Read the full article, click here.


@KirkDBorne: “What do #DataScientists do all day at work? #BigData #DataScience #MachineLearning”


Ram Narasimhan of General Electric talks about the importance of curiosity and what makes his day


What Data Scientists Do All Day at Work