Machine learning is the field of computer science where a system improves its performance on a specific task through the application of algorithmic and statistical models. In this article, we cover interesting projects in machine learning programming so far in 2018.

Though machine learning business applications already used by companies like Netflix (suggests content based on the user), Two Sigma (hedge fund that uses machine learning), AlphaGo (a program that beats world class go players) etc.

The projects featured in the list are open source projects and to ensure their quality we have also mentioned their Github rating. A Machine learning developer can use open source projects and add some of his/her own on the platform.

Find out List of Top 10 Machine Learning Projects

1) Tensorflow (117k stars and 46,390 commits on Github)

It was developed by Google in collaboration with brain team and it is used in every Google application (e.g. Google voice assistant, Google photos etc.) For machine learning. It is based on python and works like the computational library for writing new algorithms.

2) Keras (37k stars and 4950 commits on Github)

It also a python based library created with a focus for fast experimentation. If you’re a fresh machine learning developer, you can begin with this library. It provides the easiest way To include neural networks.

3) Pytext (3849 stars and 58 commits on Github)

It is deep learning based on PyTorch. You can also export via optimized Caffe2 Execution engine.

4) JAX: Autograd and XLA (2615 stars and 457 commits on Github)

JAX is the combination of Aurograd and XLA which facilitates high-performance machine Learning research. Using loops, branches, recursions and diversions it can differentiate Between Python and Numpy functions.

5) Loguru (2376 stars and 238 commits on Github)

It basically makes logging in Python simpler and enjoyable. To make the use of login application automatic it uses various functionalities.

6) BERT (10108 stars and 97 commits on Github)

BERT or Bidirectional Encoder Representation from Transformers is the method of pre-training language representations which focuses on Natural Language Processing (NLP) Tasks.

7) NeverGrad (1437 stars and 14 commits on Github)

It is a python based project which allows gradient-free optimization. It also has tools to Instruct codes and functions to test optimization of algorithms. You can also perform Benchmark routines to compare algorithms easily.

8) Home assistant (19954 stars and 16976 commits on Github)

It is an open source automation project based on Python 3 and allows to control and track all devices at home. It also provides the platform for automatic control. Featured integrations are Amazon Echo/ Alexa, Apple TV, Dark sky, Google cast, Ecobee etc.

9) Screenshot to code (11006 stars and 161 commits on Github)

It a neural network based on Tony Beltramelli’s pix2code and it transfers design mockups into static websites.

10) Imgaug (4627 stars and 930 commits on Github)

It performs image augmentation for machine learning experiments. It supports both common and exotic augmentation techniques. It supports images, heatmaps, keyboards Landmarks and bounding boxes too. Supports augmentation on multiple cores.

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