Tips To Ace Your First Machine Learning Hackathon
Imagine a sprint-like event, where anybody, right from the industry’s who’s who to a novice college graduate working in collaboration with their respective teams to create a functioning solution for the problem at hand. Hackathons are truly such electric events that form the breeding ground for such brilliant tech solutions. It also sometimes prove to be a great way to hire professionals who have the perfect mix of data science knowledge and programming skills for companies working in the areas of machine learning, artificial intelligence, and data science. The popularity of hackathons has only grown over the years. As per a survey, 32% of respondents said that hackathons are an excellent medium for learning and upskilling. Interestingly, only 6% think that the prize money is the most attractive part of a hackathon; we can safely deduce that merely participating in a hackathon as an experience is unmatched. For this article, we will be centring our discussion around machine learning hackathons. ML hackathons are different from other hackathons. They are more defined than the general coding or product-focused hackathons; the focus is more towards building a tangible product or discovery for the greater good rather than just bagging that prize money. So what if you are a machine learning enthusiast and want to kick-off your hackathon journey? Here we give you step-by-step instructions on how to start: Choosing the Base Tool Choosing the correct tool or programming language before entering a hackathon is the most basic and yet crucial step. One can choose from a slew of options available — R, Python, SAS, and Spark. For people who are new to machine learning and data science, in general, are often advised to opt for ‘safe’ Python as it is easier to learn and comes in handy with the larger ecosystem. However, all said, the focus should be on problem-solving rather than spending too much time on learning an entirely new language. Preparing Roadmap A little spadework before actually participating in a hackathon would go a long way. If you are a beginner, you could begin by attending a few workshops, undertaking a course or practising a few easy-to-do projects. You can choose among various resources available on the internet — MachineHack, Kaggle, and HackerEarth. Going through the common machine learning algorithms such as linear regression, logical regression, K-means, decision trees, and the random forest is also advised. Devising your own tips and tricks from the past competition-specific hackathons is sure to give an edge. Building the Right Team Having the right team to work and collaborate with is half the battle won. It is definitely not a standalone effort, and every participant should have complementary skill sets, meaning being a developer is not enough, you would still need people who are good with graphics, the business side of the project, backend developer, and subject matter experts. It is beneficial to form your group before entering the competition. One could do that by networking over social network platforms to get information about other participants. Once you are set on the idea that you would be working on, it could then be broken down into smaller chunks, and each teammate can be delegated the task corresponding to their area of expertise. Other Important Tips and Tricks Set realistic goals. Be honest with what you can achieve with your present skill set.Build a prototype that works and is demonstrable.Work on presentation skills. No matter how hard you work on your project, it ultimately boils down to how you present it.Do your homework and be thorough with your research. Be absolutely sure of the APIs and the libraries to be used.Prepare libraries of reusable code. This will save a lot of time. Alternatively, one could also prepare a standard set of code/functions to be used in most, if not all, of the hackathons.Dive in with a mindset of problem-solving and possible real-life applications. This gives a larger perspective to approach the project.Pay attention to building a hypothesis and workflow for better organisation.There are 24-, sometimes, 48-hour hackathons, and thus, it is crucial to take adequate breaks in between to avoid burnout.Lastly, have fun! Appreciate this opportunity to work, collaborate, and network with a diverse group of people.
Imagine a sprint-like event, where anybody, right from the industry’s who’s who to a novice college graduate working in collaboration with their respective teams to create a functioning solution for the problem at hand.  Hackathons are truly such electric events that form the breeding ground for such brilliant tech solutions. It also sometimes prove to […]
Hackathons are truly such electric events that form the breeding ground for such brilliant tech solutions.
["Active Learning", "Hackathon", "Kaggle", "Machine learning hackathon", "Machinehack", "Techgig"]
["data science", "Go", "API", "artificial intelligence", "Kaggle", "machine learning", "Machinehack", "Machine learning hackathon", "AI", "ML", "Active Learning", "Hackathon", "Techgig", "Python", "GAN", "R"]
["AI", "artificial intelligence", "machine learning", "ML", "data science", "Python", "R", "Go", "API", "GAN"]
I am a technology journalist with AIM. I write stories focused on the AI landscape in India and around the world with a special interest in analysing its long term impact on individuals and societies. Reach out to me at shraddha.goled@analyticsindiamag.com.