|
1 | | -NimbusML |
| 1 | +# NimbusML |
2 | 2 |
|
3 | | -`nimbusml` provides battle-tested state-of-the-art ML algorithms, |
4 | | -transforms and components, aiming to make them useful for all |
5 | | -developers, data scientists, and information workers and helpful in all |
6 | | -products, services and devices. The components are authored by the team |
7 | | -members, as well as numerous contributors from MSR, CISL, Bing and other |
8 | | -teams at Microsoft. |
| 3 | +`nimbusml` is a Python module that provides Python bindings for [ML.NET](https://github.com/dotnet/machinelearning). |
| 4 | + |
| 5 | +`nimbusml` aims to enable data science teams that are more familiar with Python |
| 6 | +to take advantage of ML.NET's functionality and performance. It provides |
| 7 | +battle-tested, state-of-the-art ML algorithms, transforms, and components. The |
| 8 | +components are authored by the team members, as well as numerous contributors |
| 9 | +from MSR, CISL, Bing, and other teams at Microsoft. |
9 | 10 |
|
10 | 11 | `nimbusml` is interoperable with `scikit-learn` estimators and transforms, |
11 | | -while adding a suite of highly optimized algorithms written in C++ and |
12 | | -C\# for speed and performance. `nimbusml` trainers and transforms support |
13 | | -the following data structures for the `fit()` and `transform()` methods: |
| 12 | +while adding a suite of fast, highly optimized, and scalable algorithms written |
| 13 | +in C++ and C\#. `nimbusml` trainers and transforms support the following data |
| 14 | +structures for the `fit()` and `transform()` methods: |
14 | 15 |
|
15 | 16 | - `numpy.ndarray` |
16 | 17 | - `scipy.sparse_cst` |
17 | 18 | - `pandas.DataFrame`. |
18 | 19 |
|
19 | | -In addition, `nimbusml` also supports streaming from files without loading |
20 | | -the dataset into memory, which allows training on data significantly |
21 | | -exceeding memory using `FileDataStream`. |
| 20 | +In addition, `nimbusml` also supports streaming from files without loading the |
| 21 | +dataset into memory with `FileDataStream`, which allows training on data |
| 22 | +significantly exceeding memory. |
22 | 23 |
|
23 | | -With `FileDataStream` `nimbusml` is able to handle up to **billion** features |
24 | | - and **billions** of training examples for select algorithms. |
| 24 | +With `FileDataStream`, `nimbusml` is able to handle up to a **billion** |
| 25 | +features and **billions** of training examples for select algorithms. |
25 | 26 |
|
26 | 27 | For more details, please refer to the documentation: |
27 | | -<https://docs.microsoft.com/en-us/nimbusml>. |
| 28 | +<https://docs.microsoft.com/en-us/nimbusml>. |
| 29 | + |
| 30 | +## Third party notices |
| 31 | + |
| 32 | +`nimbusml` contains ML.NET binaries and the .NET Core CLR runtime, as well as |
| 33 | +their dependencies. Both ML.NET and .NET Core CLR are made available under the |
| 34 | +MIT license. Please refer to the [third party notices](https://github.com/microsoft/NimbusML/blob/master/THIRD-PARTY-NOTICES.txt) |
| 35 | +for full licensing information for ML.NET and .NET Core CLR. |
0 commit comments