With Tensorflow 2.0 released in alpha recently, we want to bring the community upto speed with the new version of the framework. This workshop is a step in that direction! In the first session of the workshop, we introduced the participants to a typical ML pipeline and talked about various paradigms of learning (Supervised, Unsupervised, etc.). We also demo-ed three basic ML algorithms for the participants to be able to see them in action and learn the math and intuition behind them. These algorithms were: — Linear Regression — K-Nearest Neighbours — K-means clustering At the end of the session, we opened a Kaggle contest for the students to participate in and play around with what they learnt. With this session, we want to make our path towards Deep Learning, motivate it in a manner that makes the community realise the importance of Deep Learning techniques and why they are necessary. Additionally, our end goal is to bring them to a point where they can explore Deep Learning on their own with Tensorflow!
Speakers
