DataHour: How to Evaluate Your Machine Learning Model?

We regret to inform you that this session has been postponed. Will update this page soon.

About the DataHour:

In order to avoid trouble before it happens and determine which model makes the most accurate predictions, either a person or the methodology must evaluate and score each model as it is developed. Remember that the model will be exposed to unknown data once it is operationalized. Knowing evaluation metrics can help you choose the right model and determine

which metric is important for a given domain. Also, it will make it easier for you to communicate with your client and comprehend the various Machine Learning techniques. It also helps you comprehend a problem statement clearly, which helps in implementing the best machine learning solution. This quantifies the quality of the model to determine whether the achieved model is universal or biased.

In this DataHour, Juhi will explain why and how you can evaluate your machine learning model.

Prerequisites: Enthusiasm for learning 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:

Juhi Pandey

Senior Manager Data Science at EXL

Juhi Pandey is an Artificial Intelligence and Machine Learning Evangelist, a Speaker, and a Mentor. She has 13+ years of experience, statistical, and architectural experience in different domains like Life Science, Marketing, Finance and Supply Chain Management. She has a rich experience of building and scaling AI and Machine Learning businesses. She is currently working as a Senior Manager Data Scientist at EXL where she is part of the core Data Science team, working on various Machine Learning, Deep Learning, Natural Language Processing, and Artificial intelligence engagements by applying state of the art techniques in this space. She is Azure Data Science Certified and Certified Business Analysis Professional (CBAP). She is a speaker at various International Conferences .She holds a bachelor’s degree in the subject of Computer Science and currently she is pursuing Post Graduate Diploma in Sustainability Science. She is an active blogger. She engages in technical reading, blogging, answering technical queries and mentoring budding Data Scientists in her leisure time.

Connect with her on Linkedin