# Top 10 Fabric for Deep Learning (FfDL) Alternatives & Competitors **Average Rating:** 3.9/5 **Total Number of Reviews:** 5 The Artificial Neural Network Software solutions below are the most common alternatives that users and reviewers compare with Fabric for Deep Learning (FfDL). Other important factors to consider when researching alternatives to Fabric for Deep Learning (FfDL) include ease of use and reliability. The best overall Fabric for Deep Learning (FfDL) alternative is Keras. Other similar apps like Fabric for Deep Learning (FfDL) are AIToolbox, H2O, AWS Deep Learning AMIs, and NVIDIA Deep Learning GPU Training System (DIGITS). Fabric for Deep Learning (FfDL) alternatives can be found in [Artificial Neural Network Software](https://www.g2.com/categories/artificial-neural-network) but may also be in [Machine Learning Software](https://www.g2.com/categories/machine-learning) or [Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms). ## Best Paid & Free Alternatives to Fabric for Deep Learning (FfDL) - [Keras](https://www.g2.com/products/keras/reviews) - [AIToolbox](https://www.g2.com/products/aitoolbox/reviews) - [H2O](https://www.g2.com/products/h2o/reviews) - [AWS Deep Learning AMIs](https://www.g2.com/products/aws-deep-learning-amis/reviews) - [NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/products/nvidia-deep-learning-gpu-training-system-digits/reviews) - [Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/products/microsoft-cognitive-toolkit-formerly-cntk/reviews) - [PyTorch](https://www.g2.com/products/pytorch/reviews) - [Google Cloud Deep Learning Containers](https://www.g2.com/products/google-cloud-deep-learning-containers/reviews) - [TFLearn](https://www.g2.com/products/tflearn/reviews) - [Neuton AutoML](https://www.g2.com/products/neuton-automl/reviews) ## Top 10 Alternatives to Fabric for Deep Learning (FfDL) Recently Reviewed By G2 Community Browse options below. Based on reviewer data, you can see how Fabric for Deep Learning (FfDL) stacks up to the competition, check reviews from current & previous users in industries like Computer Software, Computer & Network Security, and E-Learning, and find the best product for your business. ### 1. [Keras](https://www.g2.com/products/keras/reviews) By Keras **Average Rating:** 4.6/5 **Total Reviews:** 65 Keras is a neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs Keras](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-keras) **Compare Keras with other alternatives:** - [Keras vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-keras) - [Keras vs H2O](https://www.g2.com/compare/h2o-vs-keras) - [Keras vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-keras) - [Keras vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/keras-vs-nvidia-deep-learning-gpu-training-system-digits) - [Keras vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/keras-vs-microsoft-cognitive-toolkit-formerly-cntk) - [Keras vs PyTorch](https://www.g2.com/compare/keras-vs-pytorch) - [Keras vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-keras) - [Keras vs TFLearn](https://www.g2.com/compare/keras-vs-tflearn) - [Keras vs Neuton AutoML](https://www.g2.com/compare/keras-vs-neuton-automl) ### 2. [AIToolbox](https://www.g2.com/products/aitoolbox/reviews) By AIToolbox **Average Rating:** 4.4/5 **Total Reviews:** 35 AIToolbox is a comprehensive Swift framework designed to facilitate the development and implementation of artificial intelligence algorithms. It offers a suite of AI modules that cater to various machine learning tasks, making it a valuable resource for developers and researchers working within the Swift ecosystem. Key Features and Functionality: - Graphs and Trees: Provides data structures and algorithms for constructing and manipulating graphs and trees, essential for tasks like decision-making processes and hierarchical data representation. - Support Vector Machines (SVMs): Includes tools for implementing SVMs, enabling classification and regression analysis by finding optimal hyperplanes in high-dimensional spaces. - Neural Networks: Offers components to build and train neural networks, facilitating deep learning applications such as image and speech recognition. - Principal Component Analysis (PCA): Contains modules for dimensionality reduction through PCA, aiding in data visualization and noise reduction. - K-Means Clustering: Provides algorithms for partitioning datasets into clusters, useful in pattern recognition and data mining. - Genetic Algorithms: Includes tools for optimization problems using genetic algorithms, simulating natural selection processes to find optimal solutions. Primary Value and User Solutions: AIToolbox addresses the need for a native Swift library that encompasses a broad range of AI functionalities. By integrating multiple machine learning modules into a single framework, it simplifies the development process for Swift developers, eliminating the need to rely on external libraries or languages. This consolidation enhances efficiency, promotes code consistency, and accelerates the deployment of AI-driven applications on Apple platforms. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-fabric-for-deep-learning-ffdl) **Compare AIToolbox with other alternatives:** - [AIToolbox vs Keras](https://www.g2.com/compare/aitoolbox-vs-keras) - [AIToolbox vs H2O](https://www.g2.com/compare/aitoolbox-vs-h2o) - [AIToolbox vs AWS Deep Learning AMIs](https://www.g2.com/compare/aitoolbox-vs-aws-deep-learning-amis) - [AIToolbox vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/aitoolbox-vs-nvidia-deep-learning-gpu-training-system-digits) - [AIToolbox vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/aitoolbox-vs-microsoft-cognitive-toolkit-formerly-cntk) - [AIToolbox vs PyTorch](https://www.g2.com/compare/aitoolbox-vs-pytorch) - [AIToolbox vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/aitoolbox-vs-google-cloud-deep-learning-containers) - [AIToolbox vs TFLearn](https://www.g2.com/compare/aitoolbox-vs-tflearn) - [AIToolbox vs Neuton AutoML](https://www.g2.com/compare/aitoolbox-vs-neuton-automl) ### 3. [H2O](https://www.g2.com/products/h2o/reviews) By H2O.ai **Average Rating:** 4.5/5 **Total Reviews:** 24 H2O is a tool that makes it possible for anyone to easily apply machine learning and predictive analytics to solve today's most challenging business problems, it combine the power of highly advanced algorithms, the freedom of open source, and the capacity of truly scalable in-memory processing for big data on one or many nodes. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs H2O](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-h2o) **Compare H2O with other alternatives:** - [H2O vs Keras](https://www.g2.com/compare/h2o-vs-keras) - [H2O vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-h2o) - [H2O vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-h2o) - [H2O vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/h2o-vs-nvidia-deep-learning-gpu-training-system-digits) - [H2O vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/h2o-vs-microsoft-cognitive-toolkit-formerly-cntk) - [H2O vs PyTorch](https://www.g2.com/compare/h2o-vs-pytorch) - [H2O vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-h2o) - [H2O vs TFLearn](https://www.g2.com/compare/h2o-vs-tflearn) - [H2O vs Neuton AutoML](https://www.g2.com/compare/h2o-vs-neuton-automl) ### 4. [AWS Deep Learning AMIs](https://www.g2.com/products/aws-deep-learning-amis/reviews) By Amazon Web Services (AWS) **Average Rating:** 4.4/5 **Total Reviews:** 24 The AWS Deep Learning AMIs is designed to equip data scientists, machine learning practitioners, and research scientists with the infrastructure and tools to accelerate work in deep learning, in the cloud, at any scale. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-fabric-for-deep-learning-ffdl) **Compare AWS Deep Learning AMIs with other alternatives:** - [AWS Deep Learning AMIs vs Keras](https://www.g2.com/compare/aws-deep-learning-amis-vs-keras) - [AWS Deep Learning AMIs vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-aws-deep-learning-amis) - [AWS Deep Learning AMIs vs H2O](https://www.g2.com/compare/aws-deep-learning-amis-vs-h2o) - [AWS Deep Learning AMIs vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/aws-deep-learning-amis-vs-nvidia-deep-learning-gpu-training-system-digits) - [AWS Deep Learning AMIs vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/aws-deep-learning-amis-vs-microsoft-cognitive-toolkit-formerly-cntk) - [AWS Deep Learning AMIs vs PyTorch](https://www.g2.com/compare/aws-deep-learning-amis-vs-pytorch) - [AWS Deep Learning AMIs vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/aws-deep-learning-amis-vs-google-cloud-deep-learning-containers) - [AWS Deep Learning AMIs vs TFLearn](https://www.g2.com/compare/aws-deep-learning-amis-vs-tflearn) - [AWS Deep Learning AMIs vs Neuton AutoML](https://www.g2.com/compare/aws-deep-learning-amis-vs-neuton-automl) ### 5. [NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/products/nvidia-deep-learning-gpu-training-system-digits/reviews) By NVIDIA **Average Rating:** 4.5/5 **Total Reviews:** 23 NVIDIA Deep Learning GPU Training System (DIGITS) deep learning for data science and research to quickly design deep neural network (DNN) for image classification and object detection tasks using real-time network behavior visualization. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-nvidia-deep-learning-gpu-training-system-digits) **Compare NVIDIA Deep Learning GPU Training System (DIGITS) with other alternatives:** - [NVIDIA Deep Learning GPU Training System (DIGITS) vs Keras](https://www.g2.com/compare/keras-vs-nvidia-deep-learning-gpu-training-system-digits) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-nvidia-deep-learning-gpu-training-system-digits) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs H2O](https://www.g2.com/compare/h2o-vs-nvidia-deep-learning-gpu-training-system-digits) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-nvidia-deep-learning-gpu-training-system-digits) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-nvidia-deep-learning-gpu-training-system-digits) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs PyTorch](https://www.g2.com/compare/nvidia-deep-learning-gpu-training-system-digits-vs-pytorch) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-nvidia-deep-learning-gpu-training-system-digits) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs TFLearn](https://www.g2.com/compare/nvidia-deep-learning-gpu-training-system-digits-vs-tflearn) - [NVIDIA Deep Learning GPU Training System (DIGITS) vs Neuton AutoML](https://www.g2.com/compare/nvidia-deep-learning-gpu-training-system-digits-vs-neuton-automl) ### 6. [Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/products/microsoft-cognitive-toolkit-formerly-cntk/reviews) By Microsoft **Average Rating:** 4.2/5 **Total Reviews:** 22 Microsoft Cognitive Toolkit is an open-source, commercial-grade toolkit that empowers user to harness the intelligence within massive datasets through deep learning by providing uncompromised scaling, speed and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms already use. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-microsoft-cognitive-toolkit-formerly-cntk) **Compare Microsoft Cognitive Toolkit (Formerly CNTK) with other alternatives:** - [Microsoft Cognitive Toolkit (Formerly CNTK) vs Keras](https://www.g2.com/compare/keras-vs-microsoft-cognitive-toolkit-formerly-cntk) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-microsoft-cognitive-toolkit-formerly-cntk) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs H2O](https://www.g2.com/compare/h2o-vs-microsoft-cognitive-toolkit-formerly-cntk) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-microsoft-cognitive-toolkit-formerly-cntk) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-nvidia-deep-learning-gpu-training-system-digits) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs PyTorch](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-pytorch) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-microsoft-cognitive-toolkit-formerly-cntk) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs TFLearn](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-tflearn) - [Microsoft Cognitive Toolkit (Formerly CNTK) vs Neuton AutoML](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-neuton-automl) ### 7. [PyTorch](https://www.g2.com/products/pytorch/reviews) By Jetware **Average Rating:** 4.5/5 **Total Reviews:** 22 PyTorch is an open-source machine learning framework that accelerates the transition from research prototyping to production deployment. Developed by Meta AI and now governed by the PyTorch Foundation under the Linux Foundation, PyTorch is widely used for applications in computer vision, natural language processing, and more. Its dynamic computation graph and intuitive Python interface make it a preferred choice for researchers and developers aiming to build and deploy deep learning models efficiently. Key Features and Functionality: - Dynamic Computation Graph: Allows for flexible and efficient model building, enabling changes to the network architecture during runtime. - Tensors and Autograd: Utilizes tensors as fundamental data structures, similar to NumPy arrays, with support for automatic differentiation to streamline the computation of gradients. - Neural Network API: Provides a modular framework for constructing neural networks with pre-defined layers, activation functions, and loss functions, facilitating the creation of complex models. - Distributed Training: Offers native support for distributed training, optimizing performance across multiple GPUs and nodes, which is essential for scaling large models. - TorchScript: Enables the transition from eager execution to graph execution, allowing models to be serialized and optimized for deployment in production environments. - TorchServe: A tool for deploying PyTorch models at scale, supporting features like multi-model serving, logging, metrics, and RESTful endpoints for application integration. - Mobile Support (Experimental): Extends PyTorch capabilities to mobile platforms, allowing models to be deployed on iOS and Android devices. - Robust Ecosystem: Supported by an active community, PyTorch offers a rich ecosystem of tools and libraries for various domains, including computer vision and reinforcement learning. - ONNX Support: Facilitates exporting models in the Open Neural Network Exchange (ONNX) format for compatibility with other platforms and runtimes. Primary Value and User Solutions: PyTorch's primary value lies in its ability to provide a seamless path from research to production. Its dynamic computation graph and user-friendly interface allow for rapid prototyping and experimentation, enabling researchers to iterate quickly on model designs. For developers, PyTorch's support for distributed training and tools like TorchServe simplify the deployment of models at scale, reducing the time and complexity associated with bringing machine learning models into production. Additionally, the extensive ecosystem and community support ensure that users have access to a wide range of resources and tools to address various machine learning challenges. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs PyTorch](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-pytorch) **Compare PyTorch with other alternatives:** - [PyTorch vs Keras](https://www.g2.com/compare/keras-vs-pytorch) - [PyTorch vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-pytorch) - [PyTorch vs H2O](https://www.g2.com/compare/h2o-vs-pytorch) - [PyTorch vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-pytorch) - [PyTorch vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/nvidia-deep-learning-gpu-training-system-digits-vs-pytorch) - [PyTorch vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-pytorch) - [PyTorch vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-pytorch) - [PyTorch vs TFLearn](https://www.g2.com/compare/pytorch-vs-tflearn) - [PyTorch vs Neuton AutoML](https://www.g2.com/compare/neuton-automl-vs-pytorch) ### 8. [Google Cloud Deep Learning Containers](https://www.g2.com/products/google-cloud-deep-learning-containers/reviews) By Google **Average Rating:** 4.5/5 **Total Reviews:** 21 Preconfigured and optimized containers for deep learning environments. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-google-cloud-deep-learning-containers) **Compare Google Cloud Deep Learning Containers with other alternatives:** - [Google Cloud Deep Learning Containers vs Keras](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-keras) - [Google Cloud Deep Learning Containers vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-google-cloud-deep-learning-containers) - [Google Cloud Deep Learning Containers vs H2O](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-h2o) - [Google Cloud Deep Learning Containers vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-google-cloud-deep-learning-containers) - [Google Cloud Deep Learning Containers vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-nvidia-deep-learning-gpu-training-system-digits) - [Google Cloud Deep Learning Containers vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-microsoft-cognitive-toolkit-formerly-cntk) - [Google Cloud Deep Learning Containers vs PyTorch](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-pytorch) - [Google Cloud Deep Learning Containers vs TFLearn](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-tflearn) - [Google Cloud Deep Learning Containers vs Neuton AutoML](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-neuton-automl) ### 9. [TFLearn](https://www.g2.com/products/tflearn/reviews) By TFLearn **Average Rating:** 4.0/5 **Total Reviews:** 20 TFlearn is a modular and transparent deep learning library built on top of Tensorflow that provide a higher-level API to TensorFlow in order to facilitate and speed-up experimentations, while remaining fully transparent and compatible with it. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs TFLearn](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-tflearn) **Compare TFLearn with other alternatives:** - [TFLearn vs Keras](https://www.g2.com/compare/keras-vs-tflearn) - [TFLearn vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-tflearn) - [TFLearn vs H2O](https://www.g2.com/compare/h2o-vs-tflearn) - [TFLearn vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-tflearn) - [TFLearn vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/nvidia-deep-learning-gpu-training-system-digits-vs-tflearn) - [TFLearn vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-tflearn) - [TFLearn vs PyTorch](https://www.g2.com/compare/pytorch-vs-tflearn) - [TFLearn vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-tflearn) - [TFLearn vs Neuton AutoML](https://www.g2.com/compare/neuton-automl-vs-tflearn) ### 10. [Neuton AutoML](https://www.g2.com/products/neuton-automl/reviews) By Bell Integrator **Average Rating:** 4.5/5 **Total Reviews:** 17 Neuton, an AutoML platform, allows experienced users and those without any experience in Machine Learning to build compact AI models with just a few clicks and without any coding. Neuton is based on a proprietary neural network framework invented and patented by our team of scientists that is far more effective than any other framework, non-neural algorithm on the market. Its resulting models are self-growing, much more compact, fast and require fewer training samples in comparison to those of other solutions. Categories in common with Fabric for Deep Learning (FfDL): [Artificial Neural Network](https://www.g2.com/categories/artificial-neural-network) **Compare:** [Fabric for Deep Learning (FfDL) vs Neuton AutoML](https://www.g2.com/compare/fabric-for-deep-learning-ffdl-vs-neuton-automl) **Compare Neuton AutoML with other alternatives:** - [Neuton AutoML vs Keras](https://www.g2.com/compare/keras-vs-neuton-automl) - [Neuton AutoML vs AIToolbox](https://www.g2.com/compare/aitoolbox-vs-neuton-automl) - [Neuton AutoML vs H2O](https://www.g2.com/compare/h2o-vs-neuton-automl) - [Neuton AutoML vs AWS Deep Learning AMIs](https://www.g2.com/compare/aws-deep-learning-amis-vs-neuton-automl) - [Neuton AutoML vs NVIDIA Deep Learning GPU Training System (DIGITS)](https://www.g2.com/compare/nvidia-deep-learning-gpu-training-system-digits-vs-neuton-automl) - [Neuton AutoML vs Microsoft Cognitive Toolkit (Formerly CNTK)](https://www.g2.com/compare/microsoft-cognitive-toolkit-formerly-cntk-vs-neuton-automl) - [Neuton AutoML vs PyTorch](https://www.g2.com/compare/neuton-automl-vs-pytorch) - [Neuton AutoML vs Google Cloud Deep Learning Containers](https://www.g2.com/compare/google-cloud-deep-learning-containers-vs-neuton-automl) - [Neuton AutoML vs TFLearn](https://www.g2.com/compare/neuton-automl-vs-tflearn) ## Explore Articles - [Media monitoring service with best reviews](https://www.g2.com/discussions/media-monitoring-service-with-best-reviews) - [Best MDM software for small business](https://www.g2.com/discussions/best-mdm-software-for-small-business-what-works-what-doesn-t) - [What's the best chatbot for business communications](https://www.g2.com/discussions/what-s-the-best-chatbot-for-business-communications) - [Best Payroll Software](https://www.g2.com/articles/best-payroll-software) - [Which spend management software is best for large enterprises](https://www.g2.com/discussions/which-spend-management-software-is-best-for-large-enterprises) - [Top tools for managing construction timelines](https://www.g2.com/discussions/top-tools-for-managing-construction-timelines) ## Spotlight Categories - [Communication Platform as a Service (cPaaS) Platforms](https://www.g2.com/categories/communication-platform-as-a-service) - [Virtual Data Room Software](https://www.g2.com/categories/virtual-data-room-vdr) - [Accounting Software](https://www.g2.com/categories/accounting)