Building Django applications with pre-trained ML models in the backend.

Yash Sharma (~YashSharma)


16

Votes

Description:

There are several scenarios where web applications are to be built which have to provide Machine Learning solutions. It is hard to make such applications which have to run ML models at the backend. This talk provides you with a simple and effective procedure for the same. The talk will cover both the aspects using a case study (details of which will be updated soon)

  • Developing a django app.
  • Training and hosting your own ML model
  • Connecting the two to build a fast web application to provide ML based solutions.

Prerequisites:

  • Basic understanding of MVC architecture.
    • Beginner level knowledge of Machine Learning.

Both the aspects of the talk would be covered extensively, attendees should only have a basic understanding of the same.

Content URLs:

Slides (WIP)

Speaker Info:

  • Yash Sharma is a data science enthusiast who has been following and applying state of the art ML approaches throughout his college tenure. Currently working with ZS Associates, one of the leading Consulting firm, as a Data Science Associate he is in touch with all the industry standards and ongoing developments in the field of Data Science. He completed his undergrad from IIT Roorkee in 2017 where he was involved with the building of a college based Data Science community and furthering the research and learning environment in the campus.
    • Aman Shrivastava a 2017 graduate from IIT Roorkee, has been working in the field of Web Development for the major part of his college term. He has been involved in various web based applications for audiences within the campus and out. Currently working with Citi, Pune as an Analyst, he has been involved with various web art projects including a Google Play Store Application. He has also been involved with the study of Machine Learning and is knowledgeable with various ML and DL technologies.

Speaker Links:

Github Links

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Section: Web Development
Type: Talks
Target Audience: Intermediate
Last Updated: