Kaggle’s main competitions take aspirants from the lightest to the most difficult to shape their talent
If you enjoy machine learning and data science, you must have come across the online community called Kaggle. Kaggle is the world’s largest data science network, promoting a variety of courses, books, and tutorials to educate students, professionals, and even experts. Kaggle is seen as an amazing place for people just starting their careers in machine learning and data science. But in addition to the many educational contents it offers, Kaggle also organizes contests to shape the careers of aspirants. Kaggle contests help aspiring students or candidates learn and learn more about the technological side of things and sometimes even lead to big cash prizes. Kaggle competitions are organized by the community or other companies such as Google or WHO. Everyone from beginners to advanced competition levels can participate in easy, two-step competitions with small rules, organized by Kaggle. Although Kaggle offers a lot of competition, some are very different from others. Kaggle’s high competition takes athletes from light to the most difficult and helps them develop their talents. Analytics Insight listed some of the top Kaggle contests that technicians should have in July 2021.
Main Kaggle Competition in July 2021
Titanic- Disaster Learning Machine
As mentioned above, Kaggle works to encourage beginners by putting them in easy and hard competition. The Titanic ML contest is the first example that helps avid enthusiasts dive into the many machine learning competitions and become familiar with how Kaggle works. The competition is specifically for beginners who are just starting a career in machine learning. There is a simple function of using the machine to create a model to determine which passengers survived the sinking of the Titanic. Kaggle’s contest explains the situation to the participants and they think they can solve it using technology tools.
Real Estate – Advanced regression technologies
It is not a class for beginners, but it still helps to teach young students or those interested in expanding their basic knowledge. To take the course, the candidate must have some experience with R or Python and a basic understanding of machine learning. Honest, scientific students who are passionate about machine learning and who have completed regular ML courses can participate in this competition. The construction contest challenges participants to predict sales prices and model engineering characteristics, RF, and gradient growth. They prepared 79 moving lists, described all aspects of housing in Ames, Iowa, and encouraged participants to see the final value of each home.
Technology-savvy people often try to learn all the troubles that come their way. Even machine learners can examine your computer vision. That’s what drives this competition. If the contestant has experience with R or Python and basic machine learning but is new to computer vision, the contestant will give them the opportunity to improve their computing experience. Techniques such as neural networks are introduced using a standard set-up involving pre-removal features. The contest asks participants to identify figures from a set of tens of thousands of handwritten drawings.
Cultural language processes and disturbances of Tweets
This competition introduces data scientists into an unexplored concept called natural linguistics (NLP). Even with a lack of international knowledge, participants can participate in the competition and use the popular Kaggle Notebooks Kaggle environment, without setting, for free. The contest asks participants to predict whether or not the tweets are about real disasters. Twitter has become more and more an important means of communication. Even governments use it to promote their standards and innovations. On the other hand, it is used as a quick discussion method for reporting incidents. Therefore, Kaggle challenges participants to find out if the tweet is about a natural disaster or not with the help of PNL.
I am also a painter
Each artist has their own style of giving a special touch to his or her art book. The competition uses that book to challenge participants to identify the original artist based on their unique style and build a similar design using technology. To do this, participants can receive help from computer screens. Computer vision has advanced tremendously in recent years, and GAN is now able to test things in a dynamic way. They can use an electric motor and a logo to create Monet-style images.