Machine Learning benefits many parts of our lives. However, it‘s relying on larger and larger datasets for training. Although models performs better as data sizes grow, training time also increases. To tackle this problem, our project combines cloud computing with BIDData, a state-of-the-art ML toolkit by Berkeley. We implement a novel method to parallelize training, cutting training time proportional to number of computers used.
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