Hi, I am Shagun Sodhani, a computer science graduate from Indian Institute of Technology (IIT), Roorkee. Presently, I am working with the Analytics and the Data Science team at Adobe Systems. In this role, I actively contribute to solving novel problems in the domain of Machine Learning and Natural Language Processing and developing valuable solutions for Adobe. Recently, I also won the Outstanding Young Engineers Award at Adobe Systems.
Along with my full-time commitments at Adobe, I have worked as a teaching assistant with Databricks for Data Science and Engineering with Apache® Spark™ MOOC series. The course was designed by faculty from UC Berkeley, UC Los Angeles and Databricks and was offered on the edX platform. I regularly attend tech-talks and meetups as well. I have delivered talks and workshops at events like PyCon India 2016 and Big Data Training Program, IIT Roorkee (organised by Dept. of Science and Technology, Govt. of India). Since August 2015, I have committed myself into reading and summarising one research paper every week which has helped me to develop a good understanding of Machine Learning and related domains.
Moderator note: We are very excited to have Shagun d...
Moneyball: A movie about machine learning, and its application to baseball
One of machine learning's most popular application is to pro-sports. And a lot of people who are into sports love looking at the player statistics. This movie is the story of how the Oakland's baseball team in 2002 completely overhauled their approach to select the team using numbers against the advice of the experienced scouts. They changed the game of baseball forever, for the better!
Hi Shagun, Really liked your determination of reading a research text each week. That's a nice way of keeping in touch with latest happenings in Machine Learning. Personally, I am a rookie in this field of machine learning but have experience in GPU computing using CUDA.
Hoping to learn on this forum some exciting stuff.
Overfitting: Machine Learning A Cappella - Thriller!
Towards the end of a machine learning course at Brown University, professor Michael Littman was thinking about what concept from the entire course would he want his students to remember forever. The winner was overfitting, which I would agree as being the most important concept in machine learning, after machine learning itself. So, he and his group decided to make an a-cappella on overfitting to make it more memorable. Enjoy!