Challenges in Machine Learning

Join us at NIPS 2018: CiML 2018 workshop + NIPS competition track.

​Upcoming challenges:
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AutoDL: Automatic Deep Learning challenge. Create a neural network that solves a new task, without any human intervention. A blind testing code submission challenge: [SIGN UP].
L2RPN: Help the French high voltage grid electricity company transport electricity safely to everyone. A reinforcement learning challenge: [SIGN UP].

Mission:

Machine Learning is the science of building hardware or software that can achieve tasks by learning from examples. The examples often come as {input, output} pairs. Given new inputs a trained machine can make predictions of the unknown output.

Examples of machine learning tasks include:
    • automatic reading of handwriting
    • assisted medical diagnosis
    • automatic text classification (classification of web pages; spam filtering)
    • financial predictions
We organize challenges to stimulate research in this field. The web sites of past challenges remain open for post-challenge submission as ever-going benchmarks.


ChaLearn is a tax-exempt organization under section 501(c)(3) of the US IRS code. DLN: 17053090370022.
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