Introducing Global Leaderboards

A whole new exciting way for data scientists to compete and stay motivated on MachineHack! We are thrilled to announce the launch of four new leaderboards, all designed to enhance your experience on our platform and help you grow as a data science and machine learning professional.

🎉🌐 We have revamped our Hackathon leaderboard with a fresh design and improved functionality, giving you a better view of your performance and ranking compared to your peers.

🎉🌐 Our Global Practice Leaderboard allows you to track your progress on our platform and see how you stack up against others in the MachineHack community. The more you practice, the higher you'll climb!

🎉🌐Our Global Assessments Leaderboard offers the opportunity to ace our assessments and climb up the global leaderboard for those looking to showcase their conceptual skills and expertise.

🎉🌐Our Global Blogs Leaderboard is the perfect place for content creators to share their knowledge, insights, and experience in data science and machine learning. Earn recognition and points for your contributions.

🎉🌐And finally a wonderful page that puts this all together for a brilliant and fun competitive dynamic. Check it out here.

We believe these new leaderboards will promote healthy competition, encourage growth, and foster a vibrant learning community.

Data Engineering Summit:

Data Engineering Summit (DES23), India’s first & only conference on data engineering, is a two-day in-person conference slated to be held on April 27 and 28 at Hotel Radisson Blu, Bengaluru.

Expect 700 attendees, 40+ Speakers & 300+ Organizations at the conference.

Regular Passes are expiring this week. Book your passes here.

Amazing Reads on MachineHack:

Unrolling the Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are powerful neural networks that are designed to work with sequential data. Read this article, to understand them better.

How Lagrange Multipliers Help Find the Optimal Hyperplane in SVMs?

At the core of SVMs is the concept of finding the optimal hyperplane that separates the training data into different classes. However, finding this hyperplane can be a challenging optimization problem, especially when the data is not linearly separable.

Google Brain Needs DeepMind

The Google-DeepMind partnership would be a befitting reply to Microsoft-OpenAI alliance

Happy Reading! 📚🌟