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isaacslavitt.com | ||
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tomaugspurger.net
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| | | | | This work is supported by Anaconda Inc. and the Data Driven Discovery Initiative from the Moore Foundation. Anaconda is interested in scaling the scientific python ecosystem. My current focus is on out-of-core, parallel, and distributed machine learning. This series of posts will introduce those concepts, explore what we have available today, and track the community's efforts to push the boundaries. You can download a Jupyter notebook demonstrating the analysis here. Constraints I am (or was, anyway) an economist, and economists like to think in terms of constraints. How are we constrained by scale? The two main ones I can think of are | |
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www.analyticsvidhya.com
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| | | | | This article will help finding the good features through lasso regression and getting the best algorithm through a technique called stacking. | |
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www.ethanrosenthal.com
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| | | | | How would you build a machine learning algorithm to solve the following types of problems? Predict which medal athletes will win in the olympics. Predict how a shoe will fit a foot (too small, perfect, too big). Predict how many stars a critic will rate a movie. If you reach into your typical toolkit, you'll probably either reach for regression or multiclass classification. For regression, maybe you treat the number of stars (1-5) in the movie critic question as your target, and you train a model using m... | |
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www.v7labs.com
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| | | A neural network activation function is a function that is applied to the output of a neuron. Learn about different types of activation functions and how they work. | ||
