DataHour: Implementing Gradient Descent in Python

About the DataHour:

Gradient Descent is one of the fundamental optimization algorithms which is commonly-used to train machine learning models and neural networks. Gradient descent is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. In Machine Learning, a differentiable function will be our Loss Function.

In this DataHour, Atmakumar will cover how Gradient Descent algorithm works and will further demonstrate how to create a python file and implement Gradient Descent on real world data .

Prerequisites: A basic understanding of Python programming language and interest in Data Science

Who is this DataHour for?

• Students & Freshers who want to build a career in the Data-tech domain.
• Working professionals who want to transition to the Data-tech domain.
• Data science professionals who want to accelerate their career growth

Note: E-certificates will be provided within 24 - 48 hours of the session only to those who have attended the entire webinar. Please make sure to join the zoom webinar with your correct name and email address to ensure that your certificate is properly credited to you.

Speaker:

Atmakumar Rai

Senior Data Scientist

Atmakumar has a total 5+ years of experience in the Data Science domain. He has worked on many Computer vision and NLP Projects. His interest lies in building new Models and Training them. He is currently working as Senior Data Scientist. 

Connect with him on Linkedin