#Speaker Bio-
A self-taught data scientist/analytics manager, speaker & community first-person, Kalyan has contributed to various tech communities. He enjoys being involved with these communities and helping them grow. Currently I am associated with the following groups below:
PyCon India – Review Panel Work Group Lead
PyConf Hyderabad – Organizing Committee Member
Humans for AI – Program Manager for AI learning Community
Hyderabad Python Users Group – Core Member/ Meetups Organizer
Some of the previous conference talks links -

Accepted Talks:

Neural Prophet – A powerful AI framework for Time Series Models


Neural Prophet, a new framework that extends on the original prophet framework, addresses pain points such as scale, customization and extensibility.it incorporates traditional statistical and neural network models for time series modeling, used in forecasting and anomaly detection. This is heavily inspired by Prophet, which is the popular forecasting tool developed by Facebook.


The best thing is you can get started easily using Neural Prophet. Neural Prophet is a relatively new library that uses Facebooks Prophet time series forecasting package and a Pytorch AR-Net model to produce highly accurate time series forecasts quickly. This is heavily inspired by Prophet, which is the popular forecasting tool developed by Facebook. This framework is a decomposable time series model with the components, trend, seasonality, auto-regression, special events, future regressors and lagged regressors

In this talk we are going to cover the following points:

  • Quick intro about Time Series
  • What is Neural Prophet?
  • Difference between Neural Prophet vs Prophet
  • Why we need Neural Prophet?
  • Hands on Case study (From analysis to generating forecast Models)
  • Future opportunities with NP

By the end of the talk, I will make sure, one should be able to understand this powerful framework, its usage, and benefits.