According to Statista, the value of the worldwide AI software industry is anticipated to be over US$126 billion by 2025. The current labor market is being shaped by exponential technologies, which are also creating new jobs. Hackathons have recently played a significant role in tech companies' employment practices. And with good cause.
In a matter of months, according to TAIKAI, 40% of their hackathon participants were hired by businesses. MachineHack, Kaggle, NeurIPS, and other AI/ML hackathons are the ideal venues for networking with industry insiders, collaborating with peers, and landing job offers from major tech firms. Such hackathons are well-known and well-regarded.
Competitors in these events must have a solid foundation in areas like computer languages, mathematical theories, machine learning techniques, deep learning, etc. At any ML hackathon, it all boils down to having a solid grasp of the topic. Next, thoroughly explore the sklearn package to find error metrics, model algorithms, cross-validation, and other useful information. Understand data, train, and validate; this is most critical.
Theoretical knowledge is only going to go you so far. Working on projects that allow one to put the lessons learned in a book or class into practice is more efficient than simply reading a book.
It's common to lose track of time while concentrating on fine-tuning an ML model's hyperparameters in a time-based challenge. To improve their models, the participant should invest more time in putting new concepts based on the EDA and most recent data into practice.
It's crucial to plan the model while considering the timeline. When concentrating on adjusting hyperparameters or performing cross-validation tests, etc., it is quite simple to lose track of time. You can accomplish your assignment on time if you stick to a rigid plan.
You are less likely to win a hackathon on your first try, however, it is still conceivable. To become competitive, you must have patience, learn from competitions, gather real-world experience, and build a portfolio.
Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp
_____________
Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.