Install Intel® AI Analytics Toolkit via Conda*
Intel provides access to the AI Kit through a public Anaconda repository. If you do not have an existing Conda-based python environment, install Conda and Miniconda*. To get more details on the AI Analytics Toolkit, visit the Intel AI Analytics toolkit home page.
The AI Kit product preview for Windows* currently contains the following python environment:
intel-aikit-modin for data analytics and machine learning workflows using Intel® Distribution of Modin (for accelerated Panda data frames), Intel® Extension for Scikit-learn* and Intel optimizations for XGboost (for ML training and inference)
To install the AI Kit product preview for Windows* via Conda, complete the following steps:
Activate your existing python conda environment located in <pythonhome>:
source <pythonhome>\bin\activate
For Python 3.7, install the AI Kit product preview for Windows* with the following command:
conda install intel-aikit-modin
For other Python versions, find the instructions at Intel® Distribution of Modin Getting Started Guide.
Set user environment. After the toolkit is installed, before accessing the tools, you must activate your python environment and set up environment variables to access the tools. For example, to activate the python environment created in the previous step, use:
conda activate intel-aikit-modin
List of Available Packages
NOTE:
Intel® packages are available on intel label on the Anaconda* Cloud. You must include -c intel on your command line as in the examples above, or add intel to your Conda configuration file using conda config --add channels intel.
Component Name |
Package Name |
Platform |
Channel |
|---|---|---|---|
Intel® Distribution for Python* |
intelpython3_full |
win |
intel |
Intel® Distribution of Modin* (via Anaconda distribution of the toolkit using the Conda package manager) |
intel-aikit-modin |
win |
intel |
Intel® Neural Compressor* |
neural-compressor |
win |
intel |
Intel® Optimization for PyTorch* |
pytorch (include -c pytorch on your command line) |
win |
pytorch |
Intel® Optimization for TensorFlow* |
tensorflow |
win |
intel |