Deep Learning for humans
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Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
100-Days-Of-ML-Code中文版
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Convert Machine Learning Code Between Frameworks
机器学习相关教程
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Deep learning library featuring a higher-level API for TensorFlow.
Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Scalable, event-driven, deep-learning-friendly backtesting library
CNN visualization tool in TensorFlow
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
🎆 A visualization of the CapsNet layers to better understand how it works