Going Nuts with Machine Learning

Details

Time: April 24 (Wednesday) from 6pm

Agenda:

1. Talk : Latent probabilistic Models for Document Clustering | Haridas Narayanaswamy
In this talk, the discussion will be about how one can find the latent topics from a bunch of documents without any labels (unsupervised learning). We will be covering Latent Dirichlet Allocation (LDA), a type of document clustering model. LDA can be used for multiple NLP pipelines, eg; Document clustering, topic evaluation, feature extraction, Document similarity study, text summarisation etc. Evaluating the quality of result from such unsupervised models are a challenge, we will discuss few such effective evaluation methods.

2. Talk : Computer Vision | Pallavi Ramicetty and Uttam Erukala
In this talk, we'll introduce you to computer vision technologies. We will be sharing our experience with demos and technical challenges from our experiments on image classification, object detection and segmentation, and image transformation.

3. Talk : vitaFlow | Mageswaran Dhandapani
This talk is about designing a Deep Learning model pipeline for OCR (Text Segmentation and Text Extraction) using Tensorflow, targeting domain specific information extraction

4. Networking and Snacks

What is expected from your side?
Just do an RSVP to the event and walk in, make sure to carry a govt id card.