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PLATFORMS AND PRODUCTS

TECHNOLOGY

Technology

In the emerging industry of AI/Machine Learning/Deep Learning ecosystems, we see ourselves as a leading player with our engineers contributing to the development of new trends and technologies.


TensorFlow

TensorFlow

TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks.

TensorFlowLite

TensorFlow Lite

TensorFlow Lite is an open-source deep learning framework for on-device inference. It allows deploying Machine Learning models on mobile and IoT devices.

PyTorch

PyTorch

PyTorch is an open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing. It is primarily developed by Facebook's AI Research lab.


pandas

Pandas

Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series.

plotly

Plotly

Plotly provides online graphing, analytics, and statistics tools for individuals and collaboration, as well as scientific graphing libraries for Python, R, MATLAB, Perl.

OpenCv

OpenCV

OpenCV is a library of programming functions mainly aimed at real-time computer vision. Originally developed by Intel, it was later supported by Willow Garage then Itseez. The library is cross-platform and free for use under the open-source BSD license.


unity

Unity

Unity is a cross-platform game engine developed by Unity Technologies, first announced and released in June 2005 at Apple Inc.'s Worldwide Developers Conference as a Mac OS X-exclusive game engine. As of 2018, the engine had been extended to support more than 25 platforms.

Caffe

Caffe

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors.

Docker

Docker

An open-source project that automates the deployment of applications inside software containers. Docker provides an additional layer of abstraction and automation of operating-system-level virtualization on Windows and Linux. In Enigma when possible, we try to divide each of our systems into small blocks - docker containers. We can then deploy them when needed, optionally multiplying these containers that should do some part of the data manipulation quicker, allowing for parallelism.


SciKit

SciKit

Free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Enigma’s team often prototypes models using SciKit, and when situation allows (e.g. all data fit onto one machine), we use it in the final systems as well.

XGBoost

XGBoost

Open-source software library which provides the gradient boosting framework for C++, Java, Python,R, and Julia. It works on Linux, Windows, and macOS. Other than running on a single machine, it also supports the distributed processing frameworks Apache Hadoop, Apache Spark, and Apache Flink. It is probably the most common algorithm we use - it usually, especially when dealing with business data, gives very accurate results still maintaining very quick response time, and reasonable training time.

NumPy

NumPy

Fundamental package for scientific computing with Python. It provides a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code and introduces useful linear algebra, Fourier transform, and random number capabilities. This is Enigma’s number one library for matrix operations.