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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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jakevdp.github.io
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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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research.google
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| | | [AI summary] Google's research and development efforts in software engineering, machine learning, and secure design, with a focus on advancing computer science through open-source projects, collaborative research, and innovative tools. | ||
