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TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.

It is a free online diagram software for making flowcharts, process diagrams, org charts, UML, ER and network diagrams. It is an open platform where you can create and share diagrams. It’s integrated with the tools you already use.

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

Solution for visual communication. Create online flowcharts, diagrams, UML sketches, and ER models.

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

It is an online whiteboard for teams to collaborate, brainstorm, map out flows, and more. It is easy to learn and fun to use, so anyone can participate and share their ideas.

Create flowcharts, diagrams, org charts, floor plans, engineering designs, and more, using modern shapes and templates with the familiar Office experience.

ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.

It is a suite of libraries and programs for symbolic and statistical natural language processing for English written in the Python programming language.

H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.

It is used to draw UML diagrams, using a simple and human readable text description. Be careful, because it does not prevent you from drawing inconsistent diagrams. So it's more a drawing tool than a modeling tool. It is a component that allows to quickly write Sequence diagram, Usecase diagram, Class diagram, Object diagram, Activity diagram, Component diagram, Deployment diagram, State diagram, and Timing diagram.

It is a set of tools to help developers run TensorFlow models on mobile, embedded, and IoT devices. It enables on-device machine learning inference with low latency and a small binary size.

A state-of-the-art platform for statistical modeling and high-performance statistical computation. Used for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.

It is a whiteboard tool that lets you easily sketch diagrams with a hand-drawn feel.

PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.

It is a deep learning framework made with expression, speed, and modularity in mind.

It is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Pinball.

It is the most professional and popular mind mapping tool. Millions of people use it to clarify thinking, manage complex information, run brainstorming and get work organized.

It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works.

Infuse your apps, websites and bots with intelligent algorithms to see, hear, speak, understand and interpret your user needs through natural methods of communication. Transform your business with AI today.

Caffe2 is deployed at Facebook to help developers and researchers train large machine learning models and deliver AI-powered experiences in our mobile apps. Now, developers will have access to many of the same tools, allowing them to run large-scale distributed training scenarios and build machine learning applications for mobile.

A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.

It is a software design tool tailored for agile software projects. It supports UML, BPMN, ERD, DFD, SysML. It also supports use cases, wireframeing, code engineering, etc.

It allows you to quickly create customizable UI components around your TensorFlow or PyTorch models, or even arbitrary Python functions. Mix and match components to support any combination of inputs and outputs.

Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. All you need to provide is a CSV file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest.

Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray).

It is an online mind mapping application that allows its users to visualize, share and present their thoughts via the cloud.

With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data.

It is a graphical programming interface that provides designers access to parametric modeling and data-driven customized workflows for building information modeling (BIM). It can run as an addin for Autodesk Revit and Autodesk Vasari, with the ability to manage Revit project files and family definitions, or it can run as a standalone program. It allows users to control complex geometry, construct parametric relationships, manage data, and automate tasks.

A new open source deep learning interface which allows developers to more easily and quickly build machine learning models, without compromising performance. Gluon provides a clear, concise API for defining machine learning models using a collection of pre-built, optimized neural network components.

Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK.

Create interactive user flows and stunning design presentations to engage your audience in synchronous or asynchronous design critique.

Make flowcharts, network diagrams, uml diagrams, org charts, mind maps, wireframes, and more.

This library is meant to be used with sparse, interpretable features such as those that commonly occur in search (search keywords, filters) or pricing (number of rooms, location, price). It is not as interpretable with problems with very dense non-human interpretable features such as raw pixels or audio samples.

It is an enterprise-grade predictive analysis software for business analysts, data scientists, executives, and IT professionals. It analyzes numerous innovative machine learning algorithms to establish, implement, and build bespoke predictive models for each situation.

Enables your entire team of data scientists, analysts, and developers to automatically build and deploy machine learning models on structured data at massively increased speed and scale.

Creators of Mac, iPad, and iPhone productivity software. Proud to bring you OmniFocus, OmniOutliner, OmniGraffle, and OmniPlan.

Continuous Machine Learning (CML) is an open-source library for implementing continuous integration & delivery (CI/CD) in machine learning projects. Use it to automate parts of your development workflow, including model training and evaluation, comparing ML experiments across your project history, and monitoring changing datasets.

Machine learning service that makes it easy for developers to add individualized recommendations to customers using their applications.

It translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. It offers a range of options for parallelising Python code for CPUs and GPUs, often with only minor code changes.

It is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph.

Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.