January 17 to 19 2018, Santa Clara, USA.


Speaker "Aakriti Srikanth" Details

Name :
aakriti srikanth
Company :
Title :
Product Management
Topic :

The most optimal machine learning algorithms

Abstract :

This session will help in selecting the most optimal machine learning algorithm for the particular task in hand. The session will touch upon Classification algorithms such as Logistic Regression, Support Vector Machines(SVM), Random Forest(RF) and Naives Bayes algorithms. These algorithms utilize supervised learning or label data sets for training thereby determining the right category. We will also touch upon algorithms such as Linear Regression for continuous valued functions, Collaborative filtering or Recommender functions such as Alternative Least Squares, clustering algorithms such as k-means and dimensionality reduction algorithms. Ever thought of which type of algorithm Netflix uses to make movie recommendations or Amazon uses to make product recommendations. Come find all of your answers here. Video of speaker for brief overview - Link to Aakriti’s AI video: https://youtu.be/fPuWBVgfLas

Profile :
Aakriti Srikanth is a Technical Product Manager at Red Hat(Enterprise Linux) for AI(formerly IBM Watson & Deloitte Digital: link to Aakriti’s AI video: https://youtu.be/fPuWBVgfLas), hails from the Kellogg School of Management and is currently the organizer of the Boston Data Science meetup http://meetu.ps/c/3cTyv/xCxTn/a (has about 500+ members including notable data scientists from Google, Facebook, Spotify, Amazon, IBM Watson and others). She has been involved in many of the Artificial Intelligence conferences(the AI Summit SF, MLConf, BankAI, AI World, AI Summit NYC, GraceHopper conference). With a Masters in Computer Science(specialization in AI) and as a woman in technology leader(Red Hat & formerly IBM Watson), she likes mentoring upcoming stars in AI(particularly women in AI).

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