What are good ideas for Hackathon in Machine Learning?

Machine Learning Training


Hackathons are not merely fetes where you can show off your skills but are also huge opportunities aimed at engaging gainfully and celebrating solving business issues and problems.

The Indian hackathons are corporate sponsored glitz-and-swag events where developers can compete and push boundaries by tackling industry-relevant issues in an environment that is supportive, has fireside learning, exposure to the latest gadgetry and quite like a convoluted career fair.

Job opportunities, internships, different vertical exposure, startup offers, mentorships, peer interactions, rights to brag and prizes abound. For the ML starters, it can be the pitch to learn on, join a community, hone skills, get ideas, and find the right tools and projects in coding, discover the best training and even get placed.

Take your pick from popular and reputed hackathons like MachineHack, TechGig, Hackerearth, Kaggle, and OpenML. Here are some hackathon ideas that can be advantageously used.

  1. Reach out to the online community through online ongoing hackathons where tech and ML beginners can participate, work on third-party APIs and resolutions and learn from the community. Alexa is being tweaked by Amazon in this manner.
  2. Permit multiple categories, levels, and submissions: Teams can participate in multiple category hackathons as individuals or by submitting multiple solutions at hackathons. This builds team spirit, allows multiple submissions in various categories and promotes working in communicative teams.
  3. A balanced cross-functional team yields better results: This secret in hackathons helps teams compete better, ensures better team coordination, provides a platform for the newcomers to work with the experienced and definitely satisfies learning for the whole team. Go for the prize with your team!
  4. Count results to be superior to techniques:  All hackathon participants should use their stack wisely and well, and showcase in the prototype their algorithm and skills in programming. Many a failure occurs with developing scalable models instead of the prototype, using complex databases, algorithms, and a limited stack to develop the prototype in the specified timeframe.
  5. Hackathons are about prizes for quality problems: Nobody expects a complete solution. What does impress is a simple tweak, innovation or prototype that has the potential to solve and provide a scalable solution?
  6. The product demo is essential: While the presentation has a bearing on the success and winning becomes addictive the product demo is crucial as it sums up the learning, efforts, and technology used. The real winners are those who compete and learn from their mistakes.
  7. Follow the hackathon code: The opportunity to learn should not cause problems for others. Follow the guidelines and conduct codes to provide a supportive environment for all.
  8. Exploit the learning opportunity: To break into the ML field you will need to do a machine learning course and get practical machine learning training with a reputed institute like Imarticus. Then move on to hackathons because these are events akin to sprints where hardware/software is tweaked over the next 24 to 48 hours. The skills and tasks are graded and provide participants with the chance to come up with quick solutions without needing code understanding. Do explore the workshops and 101 sessions on coding to help pick-up the requisite skills.

On a concluding note, there will be various platforms hosting events and hackathons both offline and online which provide participants for everyone.

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