Create tools and frameworks or showcase your creative ideas in the field of Machine learning and Artifical Intelligence to solve real world problems
Hack Vista is a community Hackathon organised by Codeseek for programmers and creative individuals to showcase their coding skills and their problem-solving ideas to solve real-world problems and most pressing challenges using ML/AI. Participants who have creative problem-solving ideas and knowledge on how to execute them using various Technologies without having adequate skills can also participate. We have various prizes in different areas.
₹ 25,000 in prizes
Best prototype project will receive a grand prize of Rs. 15,000 and Certificate of Achievement along with an opportunity for stipend Internship in our organization.
Best Idea (2)
The best idea will receive a grand prize of Rs.5000 and Certificate of Achievement for Best Idea along with IT accessories.
Submitting to this hackathon could earn you:
1. Attendees from all backgrounds, genders, and geographies are welcome. There is no age restriction to attend the hackathon. In case you are under 18, your parents/legal guardian should contact the hackathon to request a waiver authorizing you to attend the hackathon and submit their plan for your attendance and transportation to and from the hackathon.
2. Committee members are not eligible to participate in the hackathon. They may, however, assist teams mentors during the coding/development phase.
1. Participants who will submit their prototype or Idea will get a participation certificate for their successful project or Idea submission.
2. Winner's will get Winner's Certificate for the best project or best Idea.
3. All submission's through devpost only.
Participants will have to submit the prototype of their project via Github and video of their working model via Youtube or any other video streaming site. The prototype should be a working model.
Participants will have to submit their idea in the form of a report which should include Methodology, Technologies which can be used, Conclusion and improvements which can be made in existing model & Future scope in a form of pdf/document file.
- Machine Learning/ AI