About the challenge

In this challenge, participants will be presented with a comprehensive problem statement and a carefully curated dataset. The dataset will contain relevant features, observations, and target variables necessary for solving the problem. Participants are required to apply their expertise in data analytics and machine learning to address the challenge objectives successfully.




problem statements:

Healthcare

Analyzing medical imaging data for diagnosis and detection of diseases.

Dataset-medical image dataset

Finance:

Fraud detection in financial transactions.

dataset-creditcard dataset

Marketing and sales:

Recommender systems for books based on a person's interest.

dataset-books dataset

Enviornment science:

Crop yield prediction and precision agriculture.

dataset:Crop yield dataset

• Accuracy
  The accuracy of the machine learning model is a critical factor in evaluating its performance. Participants will be assessed based on how effectively their model predicts outcomes and makes decisions on the given dataset.
• Approach
  The methodology and strategies used by participants to tackle the AI challenge will be examined. Participants should analyze the problem, choose relevant algorithms, preprocess the data, and optimize the model.
• Video Presentation
  The video presentation should be clear, engaging, and informative. Judges will assess the ability of participants to effectively communicate their ideas, showcase their problem-solving process and model development.
• Documentation
  Participants will be evaluated on the quality and comprehensiveness of their documentation. It should include explanations of the problem, the data used, the approach taken, and the results achieved.