AVBytes: AI & ML Developments this week – Stanford’s NLP Course Projects, R Package for Anomaly Detection, Create Deep Learning Dataset, etc.

Pranav Dar 15 Apr, 2018 • 3 min read

Developments in AI & ML are happening at break neck speed. Hardly a day goes without hearing about a new development in these field. It is difficult to stay on top of these developments.

This was one of the main reasons behind launching AVBytes and the response from community has been phenomenal.

The past week saw some intriguing developments in machine learning and deep learning. Stanford released a list of all its NLP course projects for 2018 (it’s a goldmine of knowledge), the Google Research team unveiled its deep neural network to extract audio by looking at a person’s face, a R package was released to deal with anomalies in time series, and many other developments happened this week which we have covered under the AVBytes umbrella.

Scroll down to view all the articles from last week. Also, Subscribe here to get AVBytes delivered directly to your inbox daily!


Below is a round-up of all the happenings in the last week. Click on each title to read the full article.

Source: MIT Technology Review

The above AVBytes were published from 9th to 15th April, 2018.

Since I am a R user, the ‘anomalize’ package is a must-have for dealing with time series data. It makes life so much more easier! Stanford’s NLP course projects were also an eye opener – the quality of research papers released by the students is mind-boggling. What excited you the most about this week?

Subscribe here to get daily AVBytes in your inbox!


Pranav Dar 15 Apr 2018

Senior Editor at Analytics Vidhya.Data visualization practitioner who loves reading and delving deeper into the data science and machine learning arts. Always looking for new ways to improve processes using ML and AI.

Frequently Asked Questions

Lorem ipsum dolor sit amet, consectetur adipiscing elit,

Responses From Readers


Related Courses

0 Hrs 17 Lessons

Introduction to AI & ML


  • [tta_listen_btn class="listen"]