There is no substitute for experience. And that holds true in Data Science competitions as well. These cut-throat hackathons require a lot of trial-and-error, effort, and dedication to reach the ranks of the elite.
This course is an amalgamation of various talks by top data scientists and machine learning hackers, experts, practitioners, and leaders who have participated and won dozens of hackathons. They have already gone through the entire learning process and they showcase their work and thought process in these talks.
This course features top data science hackers and experts, including Sudalai Rajkumar (SRK), Dipanjan Sarkar, Rohan Rao, Kiran R and many more!
From effective feature engineering to choosing the right validation strategy, there is a LOT to learn from this course so get started today!
A working knowledge of basic machine learning algorithms will help you understand the talks covered in this course.
- About the Winning Data Science Hackathon course
- Effective Feature Engineering – A Structured Approach to Building Better ML Models - By Dipanjan Sarkar
- Automating the Machine Learning Pipeline with AutoML -By Dr. Sunil Kumar Chinnamgari
- Panel Discussion - What Sets the Top Hackers Apart?
- Top Hacks from a Kaggle Grandmaster by Pavel Pleskov
- Feature Engineering for Image Data by Aishwarya Singh & Pulkit Sharma
Automating the Machine Learning Pipeline with AutoML by Dr. Sunil Chinnamgari
AutoML and the suite of tools available in this area attempts to automate all of these tasks of a data scientist therefore enabling almost a one – click ML pipeline development. This talk attempts to introduce the concept of autoML to the participants.
What Sets the Top Hackers Apart? - A panel discussion of elite data science practitioners
A panel discussion consisting of top data scientists - Sourabh Jha, Kiran R, Mohsin Hasan Sudalai Rajkumar (SRK), Sahil Verma, Rohan Rao. They will discuss many elements of data science competitions but most importantly - What does it take to repeatedly perform well in these data science challenges?
Effective Feature Engineering for Building Better ML Models by Dipanjan Sarkar
Dipanjan takes a structured and comprehensive hands-on approach to feature engineering, where we will explore two interesting case studies based on real-world problems!
Feature Engineering for Image Data by Pulkit Sharma and Aishwarya Singh
Not all of us have unlimited resources like the big technology behemoths such as Google and Facebook. So how can we work with image data if not through the lens of deep learning? Here’s an amazing talk to up your image data skillset.
Do I need to install any software as part of the course?
No, you don’t need any software for this course. A working internet connection is enough to get you started!
Do I need to take the modules in a specific order?
No, you can pick and choose the talks you want to listen to in any order you prefer.
How long can I access the course?
Once you register, you will have 6 months to complete the course. If you visit the course 6 months after your initial registration - you will need to enroll in the course again. Your past progress will be lost.
Where can I watch all the videos from DataHack Summit?
You can checkout the full DataHack Summit 2019 talks here: