TSV
AI/ML Frameworks - TSV
AI/ML frameworks are software libraries and tools that assist in building, training, and deploying machine learning models. Various frameworks centered around Python exist, including TensorFlow, PyTorch, Keras, and Scikit-learn, catering to diverse applications such as deep learning, traditional machine learning, and edge computing. These frameworks serve as essential infrastructure for the proliferation and development of AI technology, from research and development to production deployment.
machine learning
deep learning
AI
Python
TensorFlow
PyTorch
data science
code slug name description developer language license
01 tensorflow TensorFlow An open-source machine learning framework developed by Google. Google Python, C++, CUDA Apache 2.0
02 pytorch PyTorch A machine learning framework featuring dynamic computation graphs, developed by Meta. Meta Python, C++ BSD
03 keras Keras A high-level deep learning API designed for humans. Google Python Apache 2.0
04 scikit-learn Scikit-learn A traditional machine learning library for Python. Community Python BSD
05 jax JAX A high-performance machine learning library developed by Google. Google Python Apache 2.0
06 hugging-face-transformers Hugging Face Transformers A library for natural language processing and large language models. Hugging Face Python Apache 2.0
07 xgboost XGBoost A fast and accurate gradient boosting library. Community Python, C++ Apache 2.0
08 lightgbm LightGBM A fast gradient boosting framework developed by Microsoft. Microsoft Python, C++ MIT
09 onnx ONNX An open standard for machine learning model interoperability. Microsoft, Facebook, AWS Multiple MIT
10 apache-spark-mllib Apache Spark MLlib A distributed machine learning library for large-scale data. Apache Software Foundation Python, Scala, Java Apache 2.0