Data Scientists today grapple with two problems: 1. Big Data 2. Bewildering Choice. Big Data enables data scientists to analyze more of what is available, but they cannot visualize it or explain it so easily. In addition, there is a bewildering array of tools available which means substantial work with steep learning curves to master each one of them. The solution is automation: automate what is mundane so we can focus on the most important. Here I will describe what is available in terms of Open Source and Proprietary tools for automating Data Science tasks and introduce 2 new tools: one to visualize any sized data set with one click, another: to try multiple ML models and techniques with a single call. I will provide the Github Repos for both for free in the talk.
Machine Learning Program Manager at Google, Data Scientist with deep experience in financial services and tech/media/telecom. Ram was formerly a Data Scientist at Morgan Stanley and an instructor at General Assembly & New York Institute of Finance.