While you were away attending NIPS 2017 this week, a lot has been happening around you in the data science and machine learning space.
No worries! Here is a brief roundup of the best of what we published on the Datahub this week for your weekend reading.
[box type=”shadow” align=”” class=”” width=””]If you would like to share your insights and takeaways from NIPS with our readers on the DataHub, write to us at [email protected].[/box]
NIPS 2017 Highlights – Part 1
- 3 great ways to leverage Structures for Machine Learning problems by Lise Getoor at NIPS 2017
- Top Research papers showcased at NIPS 2017 – Part 2
- Top Research papers showcased at NIPS 2017 – Part 1
Watch out for more in this area in the coming weeks.
Expert in Focus
Kate Crawford, Principal Researcher at Microsoft Research and a Distinguished Research Professor at New York University, on 20 lessons on bias in machine learning systems, Keynote at NIPS 2017
3 Things that happened this week in Data Science News
- PyTorch 0.3.0 releases, ending stochastic functions
- DeepVariant: Using Artificial Intelligence in Human Genome Sequencing
- Amazon unveils Sagemaker: An end-to-end machine learning service
For a more comprehensive roundup of top news stories this week, check out our weekly news roundup post.
Get hands-on with these Tutorials
- Understanding Streaming Applications in Spark SQL
- Implementing Linear Regression Analysis with R
- What are Slowly Changing Dimensions (SCD) and why you need them in your Data Warehouse?
