TensorFlow Alternatives

PyTorch enables fast, flexible experimentation and efficient production through a hybrid front-end, distributed training, and ecosystem of tools and libraries.

mlpack is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features.

Training Mule allows you or your team to easily label images, providing you with the datasets that you require for the best results. With your images labelled, we will train the network of your choice and provide you with the model ready for use.

Darknet: Open Source Neural Networks in C Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.

An automated AI platform, based on AutoML 2.0, for designing AI projects in a simpler and customizable way. Become agile, save yourself from staff and hardware worries, and skyrocket your business quickly.

CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R

MXNet is 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, MXNet contains a dynamic dependency scheduler that automatically parallelizes both...

Cloud AutoML helps you easily train high quality custom machine learning models with limited machine learning expertise needed.

PyCaret is an open source low-code machine learning library in Python that aims to reduce the hypothesis to insights cycle time in a ML experiment. It enables data scientists to perform end-to-end experiments quickly and efficiently.

Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs.