pydaal-tutorials

KO | EN

gitlite — search

#python #hacktoberfest #ai #machine-learning #linux #docker #macos #nodejs #java #windows #kubernetes #awesome-list #security #mcp

pydaal-tutorials

(★ 11)

Tutorials for uisng PyDAAL, i.e. the Python API of Intel Data Analytics Acceleration Library

pydaal-tutorials 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# pyDAAL Tutorials
This is a set of tutorials for uisng pyDAAL, i.e. the Python API of [Intel Data Analytics Acceleration Library](https://software.intel.com/en-us/intel-daal). 
It is designed to provide a quick introduction to pyDAAL features and the API
for Python developers who are already familiar with basic concepts and techniques in
machine learning.

The tutorials are spread across a collection of [Jupyter notebooks](http://jupyter.org/). 
The proper way of using these notebooks is to install [Intel Distribution for
Python](https://software.intel.com/en-us/intel-distribution-for-python) on your
computer, which
consists of a large set of commonly used mathematic and statistical Python
packages that are optimized for Intel architectures.

### Install Intel Distribution for Python through [conda](https://www.continuum.io/downloads)
1. Install the latest version of [Anaconda](https://www.continuum.io/downloads).
    - Choose the Python 3.5 version
2. From the shell prompt (on Windows, use **Anaconda Prompt**), execute these
   commands:

```bash
    conda config --add channels intel
    conda create --name idp intelpython3_full python=3
    source activate idp (on Linux and OS X)
    activate idp (on Windows)
    ```
More detailed instructions can be found from [this online article](https://software.intel.com/en-us/articles/using-intel-distribution-for-python-with-anaconda).

### Notebooks
* [Data management in pyDAAL](./NumericTables_example.ipynb)
* [K-Means and PCA](./kmeans_example.ipynb)
* [Linear regression](./LR_example.ipynb)
* [SVM and multi-class classifier](./SVM_example.ipynb)

Data files used in the tutorials are in the `./mldata` folder. These data files
are downloaded from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets).

pydaal-tutorials

pydaal-tutorials 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

pydaal-tutorials

pydaal-tutorials 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README