Notable changes are taking place in the ever-evolving landscape of technology employment. Once a cornerstone of technical interview preparation, LeetCode has lost its appeal. “LeetCode is designed for interview preparation, not for high-class skills,” explains Gaurav Sen, CEO of Interview Reading, a platform that focuses on system design interviews.
As a result, notable companies such as Accenture, Airtable, Betterment and Gitlab have moved from LeetCode-style interviews to a more practical real-world assessment.
The lack of AI and ML-related practice questions is another reason why LeetCode feels irrelevant for AI and ML engineers. This is where MachineHack intervene. The platform aims to empower AI developers through hackathons, community learning and comprehensive assessments, and to bridge the gap between LeetCode and ML.
MachineHack Generic AI is a complete package that allows developers to showcase their work, collaborate with other AI/ML developers, and participate in Hackathons. Unlike LeetCode, which is primarily limited to data structure algorithms (DSAs), MachineHack covers all the other essentials of ML jobs.
“We have designed MachineHack to be the ultimate package for AI/ML enthusiasts and experts. Our platform offers a holistic approach to career growth, offering everything from skill development to networking.
Dynamic Hackathon Hub
Unlike LeetCode, MachineHack is well-known for its hackathons, challenging developers to solve real problems.
So far, the platform has hosted over 200 AI hackathons, including the highly popular Data Science Student Championships and the Basha Hi-Texon (in collaboration with Google and the Government of India). MachineHack provides the perfect platform for developers to apply their skills to real-world scenarios.
“As a first-time user of MachineHack, I think it's a great platform to start your data science journey. It's user-friendly and well organized, easy access to data, send solutions, and look at the leaderboard. He said, Overall, MachineHack provided a very positive and engaging experience and “hardened my interest in data science. I'm excited to continue learning about future challenges!”
These events are supported by industry leaders eager to discover and nurture new talent. For example, the great hiring hackathon in India and the data scientists hiring Hackathon by Mathco.thon: Themathcompany are notable examples of participants having direct interaction with potential employers.
One of its outstanding events is Ideathon. How to detect AI-generated content invites participants to build tools that can flag AI-generated content with text, images, videos and audio. This Ideathon is research-oriented and captivates respected research scholars and provides a platform for deep exploratory work in AI/ML.
MachineHack, Connect Developers
Unlike popular coding platforms like LeetCode and Kaggle, MachineHack is designed to be a vibrant community where generative AI experts can share insights, learn from each other and grow together.
Akashukundu, the winner of the Video Frame Sorting Challenge, said he helped the top performers stay motivated to compete with him. “The Hackathon Grandmaster helped me to become a top-ranker while I was in the learning phase,” he added.
Narayane said target Its MachineHack promotes a support network that can connect users with mentors and peers and provide guidance, feedback and career advice. The mentorship aspect is essential for the professional growth and skill development in this rapidly evolving field of AI.
Beginner-friendly with ample space for advanced users
In many cases, platforms like Kaggle are saturated with difficult questions, and beginners can be overwhelmed by the complexity of the questions.
Narayane pointed out that MachineHack is one of the best platforms to get started with AI and ML. “We offer a variety of AI and ML courses. Additionally, participants can take part in hackathons related to AI courses, which will increase their confidence,” he added.
Himanshu Agnihotri, a Btech student at AI, agrees that the platform will help you tackle real challenges. “The platform's user-friendly setup and abundant resources made it easy to dive into problem solving. Working with a variety of data sets and tackling real challenges was exciting and fulfilling,” he added.
Filling the gap between LeetCode and AI
In addition to MachineHack, other platforms like Deep-ML also offer the UI for LeetCode in AI. “But these are relatively new projects that lack a platform to connect with hackathons, courses and other developers,” Narayane concluded.
