Top 15 Machine Learning Hackathons

Introduction

 

The popularity of machine learning has been rising every day and more people are trying to pursue it as a career. There are also many people who want to change their careers and learn data science and machine learning fast for a change. 

 

There is no alternative to hard work and practice, but there are ways that can help in making the process faster. Machine learning hackathons are one of the best ways for machine learning practitioners to practice and show their skills off to potential employers. 

 

Hackathons provide an environment for the participants to work on projects using different tools and enhance their thinking capability, networking, teamwork skills and give them a real-life experience of working under pressure, hence preparing them for their upcoming work life. 

 

In machine learning jobs, practical knowledge is very important, along with theoretical knowledge, and hackathon platforms help in achieving that. In this article, we have discussed the top 20 machine learning hackathons that can help anyone ace the game. 

 

(Must read: Machine learning courses)

 

Listing Machine Learning Hackathons

 

1. Kaggle:

 

Almost everyone in the field must have heard about Kaggle as it is the world’s largest data science platform for community and competitors with over a million registered users. It is a versatile platform as it has something for beginners, intermediate competitors, and experts. 

 

It is a crowd-sourced platform under Google that is mainly concerned with training and challenging data scientists from all around the world. It focuses on data science, machine learning, and predictive analytics.

 

At Kaggle, developers are able to host datasets, participate in running machine learning contests, and write and share codes in languages like Python, R and R markdown. 

 

There are different performance levels provided by Kaggle: Novice, Contributor, Expert, Master, and Grandmaster. There are even courses that help beginners to learn basic skills of data science and machine learning. All in all, Kaggle is a great platform for anyone who wants to delve into the field of machine learning hackathon.

 

(Must catch: Data Science projects)

 

 

2. Machine Hack:

 

Machine Hack is the creation of Analytics India Magazine which is a media portal dedicated to promoting the Data and analytics community in India. It is an online platform for competitive machine learning practice. 

 

Machine hack provides four sections for the competitors: Active hackathons, practise hackathons, rankings, and bootcamp, and four levels of performances: Apprentice, champion, master, and grandmaster.

 

Apart from Hackathons, the most intriguing aspect is the Bootcamp, which gives video lessons for studying with the assistance of professionals. 

 

Some of the great bootcamps that have been offered are "Customer Analytics in Retail," "Machine Learning in HR Using Tensorflow," "Stacking Ensembles to Solve Kaggle," etc.

 

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3. Zindi:

 

Zindi is also one of the top data science competition platforms and the first in Africa. It gives the organisations and governments access to top-notch ML and AI solutions. It has the world’s best community of scientists, engineers, teachers, organisations and governments who have accumulated together to solve the most pressing problems of Africa.

 

There are many real world problems that zindi offers, like “Lacuna- Correct field detection challenge” and “AutoInland Vehicle Insurance claim challenge” to accurately find field locatops and predict insurance submission of clients respectively. Zindi offers prize money to the winners of different competitions held by them.

 

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4. Bitgrit:

 

Bitgirt is a competitive and recruitive platform for artificial intelligence and data science where they push their esteemed data scientist community to create novel data-driven ideas to enhance AI and inculcate it into today's society across industries. 

 

It was founded in Tokyo in 2017 and has over 25,000 engineers worldwide, according to this blog written in Medium.

 

Bitgrit is an intermediate level platform that has a data science job portal for jobs in Japan. So far, three important datasets on agriculture, entertainment, and non-profit have been uploaded. 

 

From August 2019 through March 2021, 9 Challenges were held, each lasting 2–3 months. The majority of them were Optimization and Prediction Challenges with cash prizes for the top three winners.

 

 

5. Data Hack:

 

Data Hack is the brainchild of Analytics Vidhya, which has one of the top Data science communities and it is the leading machine learning knowledge portal. 

 

Analytics Vidhya hackathons are a fantastic chance for anybody interested in honing their digital abilities in areas such as artificial intelligence, machine learning, natural language processing, deep learning, business analytics, data science, big data, data visualization techniques, and so on.

 

Analytics Vidhya provides free courses and informational blogs for beginners to educate themselves and increase their skill set. There are seven editions of data science blogathons that have been conducted till date for competitors to build themselves a machine learning and data science portfolio. 

 

 

6. DrivenData:

 

DrivenData is another data science competitive platform that is for practitioners of all levels: beginner, intermediate and advanced. It sponsors data science contests to make the world a better place, offering cutting-edge prediction models to organisations solving the world's most difficult issues.

 

DrivenData generally hosts online challenges lasting for 2-3 months where a worldwide community of data scientists compete to create the best statistical and machine learning models for tough prediction issues that matter. There are also blogs for beginners to learn machine learning and data science.

 

 

7. RAMP:

 

RAMP or Rapid Analytics and Model Prototyping using Python arranges several beginner friendly data competitions and challenges that are a fantastic method to build and test machine learning algorithms collaboratively. 

 

RAMP was created as a platform for data scientists to address the data analytics component of high-impact domain scientific issues quickly and collaboratively. RAMP has gone through numerous versions since its inception, and it has also been used to train and test machine learning algorithms.

 

 

8. DPhi:

 

DPhi is a competitive community for intermediate level practitioners and coders who built a community with a vision to build data culture and democratize Data Science learning. It arranges many AI challenges that simulate real-world problems, hence bringing forward real talented and capable people who are able to provide solutions.

 

It is a great place for machine learning aspirants to polish their skills in AI, data science and machine learning through competitions and challenges. Some of the recent challenges were “Pneumonia Classification Challenge by Segmind” and “AETA Earthquake Prediction AI Algorithm Competition 2021” . DPhi also offers highly educational bootcamps for learners.

 

(Related blog: Machine learning vs data science)

 

 

9. Unearthed:

 

Unearthed is the largest network of companies, developers, and data scientists working to improve the efficiency and sustainability of the Energy and Resources business. It is appropriate for intermediate and advanced level competitors.

 

The most recent and intriguing challenge arranged by Unearthed is the "Hydrogen Hypothesis," which requires users to submit an experiment demonstrating a use case for the safe and effective usage of hydrogen in mining. Docker will be used to submit solutions to this platform. All users have access to incredible Industry use-cases.

 

 

10. DataCrunch:

 

This is another intermediate level machine learning competitive platform formed by a group of 42 ESSEC Paris students and a former finance professor who want to disrupt the hedge fund business by creating the first hedge fund controlled and owned by a community of data scientists. 

 

The DataCrunch community is for intermediate to advanced practitioners and improves the Fund's forecasts, and members are rewarded with either equity tokens (direct ownership in the Fund) or cash (200 euros for weekly challenge winners), as they choose.

 

(Suggested reading: Machine learning techniques)

 

 

11. Tianchi:

 

Tianchi is a very popular platform for intermediate and advanced level machine learning practitioners. It organizes Big Data Competitions for using big data and distributed computing resources to develop cutting-edge solutions for real-world problems. 

 

Big data, AI Ops, Machine Learning, Artificial Intelligence, Deep Learning, Object Detection, and a variety of other topics are frequently addressed in these problems, which span various disciplines.

 

(Read also: Data science applications)

 

 

12.  Numerai:

 

Numerai is a competitive platform for experts as it  promises to be the world's toughest data science competition, with the goal of creating the world's first open hedge fund by utilising Machine Learning and Predictive Modeling to model the stock market. 

 

The data science competitions organized by Numerai every week powers a real hedge fund. It also conducts forums that have experts who discuss machine learning and data science problems and their solutions. 

 

Every week, Numerai sends encrypted data to its members, who then make predictions. Then it builds a meta-model out of all of its submissions and invests.

 

 

13. Grand Challenge:

 

Grand Challenge is a framework for developing Machine Learning solutions in Bio-Medical Imaging from start to finish. This incredible platform hosts the most advanced research challenges.

 

 

14. HackerEarth:

 

HackerEarth has amassed a massive development community of over 5 million people. HackerEarth is well-known in the community for hosting over 1000 hackathons and 10,000 programming challenges to date. 

 

Using technical skill assessments and remote video interviews, the platform delivers enterprise software that assists 1000+ recruiters from organisations with their technical recruiting, according to medium. 

 

It is similar to TechGig in that it organises both live contests and hiring hackathons in areas such as data analytics, machine learning, artificial intelligence, Robotic Process Automation, design, coding, and much more.

 

 

15.  Devfolio:

 

Devfolio's aim is to assist in the development of a vibrant community of makers. InOut is India's largest community hackathon, wmn is India's largest women-only hackathon, and ETHIndia is India's largest Ethereum hackathon. 

 

Devfolio has assisted organisers in hosting over 100 hackathons across the world, including Blockchain and Fintech competitions.

 

Conclusion

 

There are other hackathons like dockship, Techgig, OpenML, etc. that serve similar purposes but we have listed the top 15 machine learning and data science hackathons that can help any learner to up their game and ace any machine learning job. 

 

It is very important for people to participate in hackathons as it helps them polish their theoretical knowledge and gain practical experience. Many companies take into consideration these hackathons, while hiring!