Check out the top 10 developers of deep learning software for 2023. Deep learning is the component of artificial intelligence that gives computers the ability to learn similarly to how people learn. Deep learning software or tools will be able to simulate how the human brain processes information and seeks out patterns to make decisions. Deep learning algorithms assist organisations in creating models that can forecast outcomes with more accuracy, enabling them to make better decisions.
DeepPy
An MIT-licensed deep learning framework is DeepPy. DeepPy is an effort to give deep learning a little bit of zen. For the majority of its calculations, DeepPy uses CUDArray. As a result, CUDArray must first be installed. It should be noted that you have the option to instal CUDArray without the CUDA back-end, which makes the process simpler.
Torch
Torch is a platform for scientific computing that prioritises GPUs and offers extensive support for machine learning methods. Because of the fast and simple scripting language LuaJIT and the underlying C/CUDA implementation, it is simple to use and effective.
OpenCV
A software library for computer vision and machine learning is called OpenCV (Open Source Computer Vision Library). In order to speed up the incorporation of artificial intelligence into commercial goods, OpenCV was created to offer a standard infrastructure for computer vision applications. OpenCV makes it simple for businesses to consume and alter the code because it is a BSD-licensed product.
Microsoft
Microsoft produces high-volume deep learning models for corporate applications. It gives data scientists and developers the tools they need to confidently and quickly construct, implement, and manage high-quality models. With industry-leading machine learning operations (MLOps), open-source interoperability, and integrated tools, it also reduces time to value.
Clarifai
The top platform for deep learning AI in computer vision, natural language processing, and automatic speech recognition is called Clarifai. It enables businesses and government organisations to understand their unstructured image, video, text, and audio data. This platform uses cutting-edge machine learning and has the largest library of pre-trained AI models available to search, sort, and organise unstructured data and assist businesses in creating turnkey AI solutions. In addition to detecting explicit content, faces, embedded objects, and language within photos, these models can also be used to predict a variety of qualities, including celebrities, food items, textures, colours, and more.
TFLearn
On top of Tensorflow, TFlearn is a modular and open-source deep learning library. It was created to give TensorFlow a higher-level API in order to facilitate and speed up experiments while still being completely open and compatible with it.
Keras
On top of the machine learning framework TensorFlow, Keras is a Python-based deep learning API. It was created with the goal of facilitating quick experimentation. Engineers and researchers can use Keras to fully use TensorFlow 2’s scalability and cross-platform capabilities because it can be run on TPU or massive GPU clusters, and Keras models can be exported for use in the browser or on mobile devices.
AWS
The infrastructure and tools needed to accelerate deep learning on the cloud at any scale are made available to machine learning practitioners and academics by the AWS Deep Learning AMIs. TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras are just a few of the well-known deep learning frameworks and interfaces that are already pre-installed on Amazon EC2 instances, allowing you to train complex, custom AI models, test out new algorithms, or pick up new knowledge and skills quickly.
AV Voice
A real-time programme receives the audio from your microphone, which is altered by AV Voice Changer before being sent. Since deep learning began to be utilised successfully, audio-visual learning, which aims to exploit the link between audio and visual modalities, has attracted a lot of attention.
Nuance
By using NVIDIA’s Automatic Mixed Precision capabilities on Volta and Turing GPUs with Tensor Cores to train its automatic speech recognition (ASR) and natural language processing (NLP) models, Nuance’s ambient clinical intelligence (ACI) technology is one example of how it is quickening the development of solutions for pressing issues in the American healthcare system.