AI
Artificial intelligence: machine learning, neural networks, large language models, deep learning, AI research, and AI tools.
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Interesting Deep Learning and NLP Projects (Stanford) cs224d.stanford.edu
, Website
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Machine Learning Interviews github.com
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fast.ai - Cutting Edge Deep Learning For Coders course.fast.ai
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Preparing and Architecting for Machine Learning gartner.com
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FairLearn fairlearn.github.io
A toolkit to assess and improve the fairness of machine learning models.
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NLP RNN Representations colah.github.io
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TFX: A tensorflow-based Production-Scale ML Platform dl.acm.org
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Testing and Debugging in Machine Learning developers.google.com
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Managing Machine Learning Projects d1.awsstatic.com
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Time series machine learning with h2o+timetk business-science.io
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CatBoost Documentation catboost.ai
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Using machine learning with LIME to understand employee churn business-science.io
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Machine learning: Moving from experiments to production blog.codecentric.de
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An Architectural Risk Analysis Of Machine Learning Systems berryvilleiml.com
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HR Analytics: Using machine learning to predict employee turnover business-science.io
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Deep learning & parameter tuning with mxnet, h2o package in R blog.hackerearth.com
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An Open Source AutoML Benchmark automl.org
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Best Practices in Machine Learning Infrastructure algorithmia.com
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Fairness Indicators: Scalable Infrastructure for Fair ML Systems ai.googleblog.com
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Responsible AI practices ai.google
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Machine Learning Using R amazon.com
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X Ruby AI group twitter.com
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Mastodon Ruby AI and Data group ruby.social
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Using the Python scikit-learn machine learning library in Ruby using PyCall practicalai.io
[code]
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Teaching an AI to play a simple game using Q-Learning in Ruby practicalai.io
[code]
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Teaching a Neural Network to play a game using Q-Learning in Ruby practicalai.io
[code]
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How to implement simple binary classification using a Neural Network in Ruby practicalai.io
[code]
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Practical Artificial Intelligence practicalai.io
Blog about Artificial Intelligence and Machine Learning with tutorials and code samples in Ruby.
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Ruby neural networks honeybadger.io
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machine_learning_workbench github.com
Framework including pure-Ruby implementations of Natural Evolution Strategy algorithms (black-box optimization), specifically Exponential NES (XNES), Separable NES (sNES), Block-Diagonal NES (BDNES) and more. Applications include neural network search/training (neuroevolution).
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