- machine_learning_examples VS stable-baselines
- machine_learning_examples VS polyaxon
- machine_learning_examples VS neptune-client
- machine_learning_examples VS d2l-en
- machine_learning_examples VS applied-ml
- machine_learning_examples VS spaCy
- machine_learning_examples VS Ray
- machine_learning_examples VS neptune-contrib
Machine_learning_examples Alternatives
Similar projects and alternatives to machine_learning_examples
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stable-baselines
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
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polyaxon
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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neptune-client
:ledger: Experiment tracking tool and model registry
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d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
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applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
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spaCy
💫 Industrial-strength Natural Language Processing (NLP) in Python
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Ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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neptune-contrib
This library is a location of the LegacyLogger for PyTorch Lightning.
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