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isaacslavitt.com | ||
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lukesingham.com
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| | | | | This post goes through a binary classification problem with Python's machine learning library scikit-learn. | |
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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.khanna.law
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| | | You want to train a deep neural network. You have the data. It's labeled and wrangled into a useful format. What do you do now? | ||
