DataHour: Think like a Data Scientist

DataHour Recording

About the DataHour:

A major challenge that every data scientist faces today is computational power. Companies want professionals who can extract predictions from the raw data cost-effectively. To get the predictions right, the data scientists have to treat the raw data well and extract necessary features for the model of their choice. Choosing the model and empowering it with the necessary optimization is one way to arrive at a more number of truly positive predictions is a very generic thought. 

Improving the accuracy of a model does not necessarily imply making the model more robust, and hence we bring back our attention to the features supplied to the model. Advanced Feature Engineering is a crucial thought process to improve the ability of your model to predict well. To think about feature engineering and to effectively perform an analysis, domain knowledge plays a key role. In this DataHour, you would learn practically about the thought process every data scientist should possess to make the machine learning models more robust.

Prerequisites:  This DataHour requires minimal exposure to a data science framework and basic terminology in data analytics.

Who is this DataHour for?

• Students and professionals looking to expand their data science knowledge base.
• Data science professionals who want to accelerate their career growth.

Speaker:

Anudeep Sri B.

Graduate Research Assistant at University of Massachusetts Dartmouth

• 6 years of experience driving any size and format of data towards insights and predictions using Azure cloud services, Bigdata and AI.
• Led a team of 11, had been a part of huge teams and had the experience of working independently for a product in the start-up environment.
• 2 years of mentoring fellow IT professionals in AI real-time case studies as part of the PGP program of UT Austin. Mentored 127 IT professionals in progressing their careers.
• Delivered 21 guest lectures on AI & Cloud Computing at various international platforms and Universities
• You can follow him on Linkedin, Twitter, Github and Youtube.