A number of new impactful open source projects have been released lately.
Open Source Data Science Projects
- Pythia – from Facebook for deep learning with vision and language, “such as answering questions related to visual data and automatically generating image captions “
- InterpretML – from Microsoft, ” package for training interpretable models and explaining blackbox systems “
- ML framework for Julia – from Alan Turing Institute, MLJ is a machine learning toolbox for Julia
- Plato – a conversational AI platform from Uber
Is the list missing a project released in 2019? If so, please leave a comment.
The Real Data on Facebook vs. Google+ is a great article about the popularity of different social networks. All the big social networks (Twitter, Facebook, Google+, LinkedIn, Pinterests, and even Myspace) are included. If you have ever wondered whether Google+ is dead or not, this article will help you out. After the data was gathered and analyzed, it is clear that Facebook is currently winning the social media battle.
The best part of the article is an interactive infographic. You can change the view of the infographic for different years and different business segments. Here is a direct link to just the Interactive Infographic, Facebook Dominates Social Networking.
- LinkedIn They turn data into products better than anyone else.
- Facebook If you are the type of person that loves to analyze people’s lives, there is no better place.
- Twitter Duh, It’s Twitter. lots of data and lots of possibilities
- Cloudera Cloudera is a successful Hadoop-based startup. Build tools and explore huge datasets for a variety of industries.
- Kaggle If optimizing algorithms and really diving into the data to get every last ounce of information is your thing, then Kaggle is it. Plus, there is nowhere else you will get to work on so many important problems in such a wide range of domains. Unfortunately, Kaggle is not currently hiring any data scientists, but they most likely will be seeking more in the future.
There are many other companies hiring data scientists. Where would you like to be a data scientist?
Marketers should target customers that share a lot on social networks. Or not! I found it interesting that Twitter and Facebook were in the bottom 5 list of influences for the social consumer. I would have expected it to be different. Search results, brand websites and online adds are all more important. This is one example of data going contrary to my own belief.