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[DOC] Updated readme and contributing files #1284

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Updated readme and contributing files
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21 changes: 18 additions & 3 deletions CONTRIBUTING.md
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Expand Up @@ -16,17 +16,28 @@
*******************************************************************************/-->

# How to Contribute
We welcome community contributions to Intel(R) oneAPI Data Analytics Library. If you have an idea how to improve the product, you can:
We welcome community contributions to Intel(R) oneAPI Data Analytics Library. You can:

* Let us know about your proposal via [Issues on oneDAL GitHub\*](https://github.com/oneapi-src/oneDAL/issues).
* Contribute your changes directly to the repository through [pull request](#pull-requests).
- Submit your changes directly with a [pull request](https://github.com/oneapi-src/oneDAL/pulls).
- Log a bug or make a feature request with an [issue](https://github.com/oneapi-src/oneDAL/issues).

Refer to our guidelines on [pull requests](#pull-requests) and [issues](#issues) before you proceed.

## Issues

Use [GitHub issues](https://github.com/oneapi-src/oneDAL/issues) to:
- report an issue
- make a feature request

**Note**: To report a vulnerability, refer to [Intel vulnerability reporting policy](https://www.intel.com/content/www/us/en/security-center/default.html).

## Pull Requests

To contribute your changes directly to the repository, do the following:
- Make sure you can build the product and run all the examples with your patch.
- Make sure your code is in line with our [coding style](#code-style) as `clang-format` is one of the checks in our public CI.
- For a larger feature, provide a relevant example.
- [Document](#documentation-guidelines) your code.
- [Submit](https://github.com/oneapi-src/oneDAL/pulls) a pull request into the `master` branch.

Public and private CIs are enabled for the repository. Your PR should pass all of our checks. We will review your contribution and, if any additional fixes or modifications are necessary, we may give some feedback to guide you. When accepted, your pull request will be merged into our GitHub* repository.
Expand All @@ -49,6 +60,10 @@ Refer to [ClangFormat documentation](https://clang.llvm.org/docs/ClangFormat.htm

For your convenience we also added [coding guidelines](http://oneapi-src.github.io/oneDAL/contribution/coding_guide.html) with examples and detailed descriptions of the coding style oneDAL follows. We encourage you to consult them when writing your code.

## Documentation Guidelines

oneDAL uses `Doxygen` for inline comments in public header files that are used to build the API reference and `reStructuredText` for the Developer Guide. See [oneDAL documentation](https://oneapi-src.github.io/oneDAL/) for reference.

---
**Note:** oneDAL is licensed under [Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0). By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.

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63 changes: 38 additions & 25 deletions README.md
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* limitations under the License.
*******************************************************************************/-->

# Intel® oneAPI Data Analytics Library
# Intel&reg; oneAPI Data Analytics Library <!-- omit in toc -->

[Installation](#installation)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Documentation](http://oneapi-src.github.io/oneDAL/)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Examples](#examples)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Get Help](https://software.intel.com/en-us/forums/intel-data-analytics-acceleration-library)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[How to Contribute](CONTRIBUTING.md)&nbsp;&nbsp;&nbsp;
[Installation](#installation)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Documentation](#documentation)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Examples](#examples)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Samples](#samples)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[Get Help](https://software.intel.com/en-us/forums/intel-data-analytics-acceleration-library)&nbsp;&nbsp;&nbsp;|&nbsp;&nbsp;&nbsp;[How to Contribute](CONTRIBUTING.md)&nbsp;&nbsp;&nbsp;

[![Build Status](https://dev.azure.com/daal/DAAL/_apis/build/status/oneapi-src.oneDAL?branchName=master)](https://dev.azure.com/daal/DAAL/_build/latest?definitionId=5&branchName=master) ![License](https://img.shields.io/github/license/oneapi-src/oneDAL.svg)

Expand All @@ -26,23 +26,20 @@ Intel&reg; oneAPI Data Analytics Library (oneDAL) is a powerful machine learning
Intel&reg; oneAPI Data Analytics Library is an extension of Intel&reg; Data Analytics Acceleration Library (Intel&reg; DAAL).


## Table of Contents
- [Build yours high-performance data science application with intel&reg; oneDAL](#build-yours-high-performance-data-science-application-with-intel-onedal)
## Table of Contents <!-- omit in toc -->
- [Python API](#python-api)
- [Scikit-learn patching](#scikit-learn-patching)
- [Distributed multi-node mode](#distributed-multi-node-mode)
- [Scikit-learn patching](#scikit-learn-patching)
- [Distributed multi-node mode](#distributed-multi-node-mode)
- [oneDAL Apache Spark MLlib samples](#onedal-apache-spark-mllib-samples)
- [Installation](#installation)
- [Installation from Source](#installation-from-source)
- [Examples](#examples)
- [Samples](#samples)
- [Documentation](#documentation)
- [Technical Preview Features](#technical-preview-features)
- [oneDAL and Intel&reg; DAAL](#onedal-and-intel-daal)

## Build yours high-performance data science application with intel&reg; oneDAL

Intel&reg; oneDAL uses all capabilities of Intel&reg; hardware, which allows you to get an significant performance boost on the classic machine learning algorithms.
## Build yours high-performance data science application with oneDAL <!-- omit in toc -->

oneDAL uses all capabilities of Intel&reg; hardware, which allows you to get an significant performance boost on the classic machine learning algorithms.

We provide highly optimized algorithmic building blocks for all stages of data analytics: **preprocessing**, **transformation**, **analysis**, **modeling**, **validation**, and **decision making**.

Expand All @@ -51,17 +48,17 @@ The current version of oneDAL provides Data Parallel C++ (DPC++) API extensions
The size of the data is growing exponentially, as is the need for high-performance and scalable frameworks to analyze all this data and extract some benefits from it.
Besides superior performance on a single node, the oneDAL distributed computation mode also provides excellent strong and weak scaling (check charts below).

Intel&reg; oneDAL K-means fit, strong scaling result | Intel&reg; oneDAL K-means fit, weak scaling results
oneDAL K-means fit, strong scaling result | oneDAL K-means fit, weak scaling results
:-------------------------:|:-------------------------:
![](docs/readme-charts/Intel%20oneDAL%20KMeans%20strong%20scaling.png) | ![](docs/readme-charts/intel%20oneDAL%20KMeans%20weak%20scaling.png)

>*technical details: FPType: float32; HW: Intel Xeon Processor E5-2698 v3 @2.3GHz, 2 sockets, 16 cores per socket; SW: Intel® DAAL (2019.3), MPI4Py (3.0.0), Intel® Distribution Of Python (IDP) 3.6.8; Details available in the article https://arxiv.org/abs/1909.11822*

Check out our [examples](#examples) and [documentation](#documentation) for information about our API
Refer to our [examples](#examples) and [documentation](#documentation) for more information about our API.

## Python API

Intel&reg; oneDAL has a python API that is provided as a standalone python library called [daal4py](https://github.com/IntelPython/daal4py).
oneDAL has a python API that is provided as a standalone python library called [daal4py](https://github.com/IntelPython/daal4py).
Below is an example of how daal4py can be used for calculation KMeans clusters

```python
Expand All @@ -85,7 +82,7 @@ result = alg.compute(data, centroids)

Python interface to efficient Intel® oneDAL provided by daal4py allows one to create scikit-learn compatible estimators, transformers, clusterers, etc. powered by oneDAL which are nearly as efficient as native programs.

| *Speedups of Intel&reg; oneDAL powered Scikit-learn over the original Scikit-learn, 28 cores, 1 thread/core* |
| *Speedups of oneDAL powered Scikit-learn over the original Scikit-learn, 28 cores, 1 thread/core* |
|:--:|
| ![](docs/readme-charts/IDP%20scikit-learn%20accelearation%20compared%20with%20stock%20scikit-learn.png) |
| *technical details: FPType: float32; HW: Intel(R) Xeon(R) Platinum 8276L CPU @ 2.20GHz, 2 sockets, 28 cores per socket; SW: scikit-learn 0.22.2, Intel® DAAL (2019.5), Intel® Distribution Of Python (IDP) 3.7.4; Details available in the article https://medium.com/intel-analytics-software/accelerate-your-scikit-learn-applications-a06cacf44912* |
Expand Down Expand Up @@ -164,7 +161,7 @@ alg = d4p.kmeans(nClusters = 10, maxIterations = 50, fptype = "float",
result = alg.compute(data, centroids)
```

For more details browse our [daal4py documentation](https://intelpython.github.io/daal4py/).
For more details browse [daal4py documentation](https://intelpython.github.io/daal4py/).

## oneDAL Apache Spark MLlib samples

Expand All @@ -183,10 +180,10 @@ You can install oneDAL:
- from [oneDAL home page](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onedal.html) as a part of Intel&reg; oneAPI Base Toolkit.
- from [GitHub\*](https://github.com/oneapi-src/oneDAL/releases).

### Installation from Source
### Installation from Source <!-- omit in toc -->
See [Installation from Sources](INSTALL.md) for details.

## Examples
## Examples <!-- omit in toc -->

Except C++ and Python API oneDAL also provide API for C++ SYCL and Java languages. Check out tabs below for more examples.
- [C++](https://github.com/oneapi-src/oneDAL/tree/master/examples/daal/cpp)
Expand All @@ -196,14 +193,15 @@ Except C++ and Python API oneDAL also provide API for C++ SYCL and Java language
- [Python](https://github.com/IntelPython/daal4py/tree/master/examples)

## Documentation
- [Get Started](http://oneapi-src.github.io/oneDAL/getstarted.html)
- [System Requirements](https://software.intel.com/content/www/us/en/develop/articles/system-requirements-for-oneapi-data-analytics-library.html)
- [oneDAL documentation](http://oneapi-src.github.io/oneDAL/)
- [Get Started Guide](http://oneapi-src.github.io/oneDAL/getstarted.html)
- [Developer Guide](http://oneapi-src.github.io/oneDAL/)
- [daal4py documentation](https://intelpython.github.io/daal4py/)
- [Specification](https://spec.oneapi.com/versions/latest/elements/oneDAL/source/index.html)
- [Release Notes](https://software.intel.com/content/www/us/en/develop/articles/oneapi-dal-release-notes.html)
- [Known Issues](https://oneapi-src.github.io/oneDAL/notes/known_issues.html)

## Samples
## Samples <!-- omit in toc -->
Samples is an examples of how oneDAL can be used in different applications.
- [Apache Arrow](https://github.com/oneapi-src/oneDAL/tree/master/samples/daal/cpp/arrow)
- [KDB](https://github.com/oneapi-src/oneDAL/tree/master/samples/daal/cpp/kdb)
Expand All @@ -216,11 +214,13 @@ Samples is an examples of how oneDAL can be used in different applications.
## Technical Preview Features

Technical preview features are introduced to gain early feedback from developers. A technical preview feature is subject to change in the future releases. Using a technical preview feature in a production code base is therefore strongly discouraged.

In C++ APIs, technical preview features are located in `daal::preview` and `oneapi::dal::preview` namespaces. In Java APIs, technical preview features are located in packages that have the `com.intel.daal.preview` name prefix.

The preview features list:
- Graph Analytics:
- Undirected graph without edge and vertex weights (undirected_adjacency_array_graph) - 32bit vertex index only
- Jaccard Similarity Coefficients for all vertex pairs, a batch algorithm which processes the graph by blocks
- Undirected graph without edge and vertex weights (`undirected_adjacency_array_graph`), where vertex indices can only be of type int32
- Jaccard Similarity Coefficients for all pairs of vertices, a batch algorithm that processes the graph by blocks

## oneDAL and Intel&reg; DAAL

Expand All @@ -230,5 +230,18 @@ This repository contains branches corresponding to both oneAPI and classical ver

|Product|Latest release|Branch|Resources|
|-------|--------------|------|:-------------:|
|oneDAL |2021.1-beta08|[master](https://github.com/oneapi-src/oneDAL)</br>[rls/onedal-beta08-rls](https://github.com/oneapi-src/oneDAL/tree/rls/onedal-beta08-rls)|&nbsp;&nbsp;&nbsp;[Home page](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onedal.html)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[Documentation](http://oneapi-src.github.io/oneDAL/)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[System Requirements](https://software.intel.com/content/www/us/en/develop/articles/system-requirements-for-oneapi-data-analytics-library.html)|
|Intel&reg; DAAL|2020 Gold|[rls/daal-2020-u2-rls](https://github.com/oneapi-src/oneDAL/tree/rls/daal-2020-u2-rls)|&nbsp;&nbsp;&nbsp;[Home page](https://software.intel.com/content/www/us/en/develop/tools/data-analytics-acceleration-library.html)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[Developer Guide](https://software.intel.com/content/www/us/en/develop/documentation/daal-programming-guide/top.html)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[System Requirements](https://software.intel.com/content/www/us/en/develop/articles/intel-data-analytics-acceleration-library-2020-system-requirements.html)|
|oneDAL |2021.1-beta10|[master](https://github.com/oneapi-src/oneDAL)</br>[rls/onedal-beta10-rls](https://github.com/oneapi-src/oneDAL/tree/rls/onedal-beta10-rls)|&nbsp;&nbsp;&nbsp;[Home page](https://software.intel.com/content/www/us/en/develop/tools/oneapi/components/onedal.html)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[Documentation](http://oneapi-src.github.io/oneDAL/)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[System Requirements](https://software.intel.com/content/www/us/en/develop/articles/system-requirements-for-oneapi-data-analytics-library.html)|
|Intel&reg; DAAL|2020 Update 3|[rls/daal-2020-u3-rls](https://github.com/oneapi-src/oneDAL/tree/rls/daal-2020-u3-rls)|&nbsp;&nbsp;&nbsp;[Home page](https://software.intel.com/content/www/us/en/develop/tools/data-analytics-acceleration-library.html)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[Developer Guide](https://software.intel.com/content/www/us/en/develop/documentation/daal-programming-guide/top.html)&nbsp;&nbsp;&nbsp;</br>&nbsp;&nbsp;&nbsp;[System Requirements](https://software.intel.com/content/www/us/en/develop/articles/intel-data-analytics-acceleration-library-2020-system-requirements.html)|

## Contribute <!-- omit in toc -->

See [CONTRIBUTING](CONTRIBUTING.md) for more information.

## License <!-- omit in toc -->

Distributed under the Apache License 2.0 license. See [LICENSE](LICENSE) for more
information.

## Security <!-- omit in toc -->

To report a vulnerability, refer to [Intel vulnerability reporting policy](https://www.intel.com/content/www/us/en/security-center/default.html).