ML Olympiad returns with greater than 20 challenges
3 min readFamous ml olympiad is again for its third spherical with over 20 community-organized machine studying competitions on Kaggle.
The ML Olympiad – organized by teams together with ML GDE, TFUG, and different ML communities – goals to offer builders with sensible alternatives to study and observe machine studying expertise by tackling real-world challenges.
In the final two rounds, a formidable 605 groups participated in 32 competitions, producing 105 discussions and 170 notebooks.
This yr’s lineup consists of challenges spanning areas equivalent to well being care, sustainability, pure language processing (NLP), laptop imaginative and prescient and extra. Competitions are organized by professional teams and builders from all over the world.
This yr’s challenges are as follows:
- Smoking detection in sufferers
Organized by Rishiraj Acharya (AI/ML GDE) in collaboration with TFUG Kolkata, the competitors duties individuals with predicting smoking standing utilizing bio-signal ML fashions.
Organized by Anas Lahdhiri beneath MLACT, this problem requires the event of a classification mannequin to differentiate between jellyfish and plastic air pollution in ocean imagery.
- Find Hallucinations in LLM
Luca Massarone (AI/ML GDE) presents a novel problem of figuring out hallucinations within the solutions offered by the Mistral 7B instruction mannequin.
Anushka Raj, with TFUG Hajipur, explores ML options to scale back meals wastage, a critical concern in immediately’s world.
Organized by Ankit Kumar Verma and TFUG Prayagraj, the competitors includes predicting physique fats share in males utilizing a number of regression strategies.
Ayush Morbar of Offbeats Bite Labs invited individuals to construct a regression mannequin to foretell the age of crabs.
TFUG Nashik challenges individuals to forecast climate situations in Nashik, India by leveraging machine studying methods.
- Prediction of earthquake harm
Usha Rengaraju presents the work of predicting the extent of injury brought about to buildings on account of earthquakes based mostly on numerous elements.
- Bangladesh climate forecast
TFUG Bangladesh (Dhaka) goals to foretell rainfall, common temperature and wet days for a specific day in Bangladesh.
- CO2 emissions prediction problem
Shahryar Azad Ivan, MD, TFUG North Bengal, and Shuvro Pal need to predict per capita CO2 emissions for 2030 utilizing world improvement indicators.
Kuan Hung (AI/ML GDE) challenges individuals to foretell mortgage approval standing, addressing an necessary facet of economic inclusion.
Ashwin Raj and BeyondML tasked individuals with predicting the liveability scores of properties, selling sustainable city improvement.
- Toxic Language Detection (PTBR)
Hosted in Brazilian Portuguese, the problem featured Mikayeri Ohana, Pedro Gengo and Vinicius F. Including classifying poisonous tweets by CARIDA (AI/ML GDE).
- enhancing catastrophe response
Yara Armel Desire of TFUG Abidjan invitations individuals to foretell humanitarian support contributions in response to disasters all over the world.
Karthikeya Rawat of TFUG Durg known as for the event of predictive fashions to estimate visitors density in city areas.
- Know your buyer’s opinion
TFUG Surabaya presents the problem of classifying buyer opinions into Likert scale classes.
- India climate forecast
Mohammed Moinuddin and TFUG Hyderabad tasked individuals to foretell temperatures for particular months in India.
The competitors, organized by TFUG Bhopal, includes creating classification fashions to foretell tumor malignancy.
- AI-Powered Job Description Generator
Akash Tripathi from TFUG Ghaziabad challenged the individuals to construct a system that routinely generates job descriptions utilizing generative AI and chatbot interface.
- Machine translation French-Wolof
GalsanAI addresses the problem of precisely translating French sentences into Wolof, offering a platform to boost language translation capabilities.
- Water Mapping Using Satellite Imagery
Taha Bohsin of ML Nomads tasked the individuals with water mapping utilizing satellite tv for pc imagery to detect dam drought.
Google is supporting each group host via this section Google for builders Program.
Participants are inspired to seek for “ML Olympiad” kagalFollow #MLOlympiad on social media, and be a part of the competitions that curiosity them most.
With such a various vary of real-world machine studying challenges, the ML Olympiad presents a superb alternative for builders to check their expertise and acquire precious expertise.
(Image credit score: Google)
See additionally: Microsoft: China plans to disrupt elections with AI-generated disinformation
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