Topic 5- "Recommendation" Text data, Cosine Similarity, word embeddings,Azure ML

We will build a recommendation engine using Text Data, Cosine Similarity and word embeddings . We will build and deploy the model in Azure using Azure ML. We will use a dataset from Kaggle (https://www.kaggle.com/c/data-science-for-good-careervillage/overview) to demonstrate this. This session will focus on, Build a recommendation engine using Text Data, Cosine Similarity and word embeddings. The model will be built and deployed in Azure using Azure ML.

Speaker BIO- Ambarish is a Business and Technology Consultant for more than 20 Years. He is a data lover and compete regularly in data science competitions. He had won Eight Data Science Competition Awards ( 1 sponsored by NASA, Seven sponsored by Kaggle - A Google Company). He presently works with Tata Consultancy Services (TCS) as the Energy Trading and Risk Management Lead, as well as Data Analytics Practice Lead for TCS Utilities. This is a very exciting position where he has the opportunity to combine domain knowledge with data. He is very fortunate to be surrounded by very enthusiastic and energetic people. He do follow cricket, loves to read detective books, and also watch detective films.
Social Handles-
LinkedIn- https://www.linkedin.com/in/ambarish-ganguly/
Twitter- https://twitter.com/a_ganguly/

Pre-requisites:
Please follow the link below:

https://ambarishg.github.io/posts/recommender-career-spacy/