The AI Tools include:

• Intel® Distribution for Python*: Achieve near-native code performance with this set of essential packages optimized for high-performance numerical and scientific computing.
• Intel® Extension for PyTorch* (CPU & GPU): Intel® Extension for PyTorch* extends PyTorch* with the latest performance optimizations for Intel hardware.
• Intel® Extension for TensorFlow* (CPU & GPU): A heterogeneous, high performance deep learning extension plugin that allows users to flexibly plug an XPU into TensorFlow* on-demand, exposing the computing power inside Intel’s hardware.
• JAX*: A Python library designed for high performance array computation.
• Intel® Optimization for XGBoost*: This well-known machine-learning package for gradient-boosted decision trees includes seamless, drop-in acceleration for Intel® architectures to significantly speed up model training and improve accuracy for better predictions.
• Intel® Extension for Scikit-learn*: A seamless way to speed up your Scikit-learn application using the Intel® oneAPI Data Analytics Library (oneDAL).

  Patching scikit-learn makes it a well-suited machine learning framework for dealing with real-life problems.

• Modin*: Enables you to seamlessly scale preprocessing across multi nodes using this intelligent, distributed dataframe library with an identical API to pandas.
• Intel® Neural Compressor: Reduce model size and speed up inference for deployment on CPUs or GPUs. The open source library provides a framework-independent API to perform model compression techniques such as quantization, pruning, and knowledge distillation.
• ONNX Runtime*: AI engine for faster inferencing and training.
• OpenVINO™ Toolkit: Convert and optimize models trained using popular frameworks like TensorFlow and PyTorch. Optimize and deploy with best-in-class performance across a mix of Intel CPUs, GPUs (integrated or discrete), NPUs, or FPGAs.
• Intel® Gaudi® Software: Efficiently map models developed using PyTorch and TensorFlow onto Intel Gaudi AI accelerators. The software suite includes a graph compiler and runtime, a Tensor Processor Core (TPC)* kernel library, firmware and drivers, and developer tools for custom kernel development and profiling.

• Configure Your System - AI Tools
  
• Build and Run a Sample Using the Command Line
  
• Notices and Disclaimers