What is Machine Learning?

Machine learning is the study of how computers can learn complex concepts from data and experience, and seeks to answer the fundamental research questions underpinning the challenges outlined above. The field of machine learning crosses a wide variety of disciplines that use data to find patterns in the ways both living systems, such as the human body and artificial systems, such as robots, are constructed and perform. Whether it’s being applied to analyze and learn from medical data, or to model financial markets, or to create autonomous vehicles, machine learning builds and learns from both algorithms and theory to understand the world around us and create the tools we need and want.

How does Kaggle Competitions Work?

Companies and organizations prepare the data and a description of the problem. Kaggle frames the competition, anonymizes the data, and integrates the winning model into their operations. Participants, like you, experiment with different techniques and compete against each other to produce the best models. Work is shared publicly through Kaggle Scripts to achieve a better benchmark and to inspire new ideas. Submissions are made through Scripts or through private manual upload. For most competitions, submissions are scored immediately (based on their predictive accuracy relative to a hidden solution file) and summarized on a live leaderboard.

What are the best schools for Machine Learning?

Carnegie Mellon University, University of Michigan Ann Arbor, Cornell, Berkeley, Stanford, Columbia University are some of the best schools for Machine Learning

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MS in Machine Learning: Top Schools

Get proven tips to increase your admission chances at top 16 schools for Master’s (MS) in Machine Learning for a global career