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Description
Neuralhub is a platform designed to streamline the process of working with neural networks, catering to AI enthusiasts, researchers, and engineers who wish to innovate and experiment in the field of artificial intelligence. Our mission goes beyond merely offering tools; we are dedicated to fostering a community where collaboration and knowledge sharing thrive. By unifying tools, research, and models within a single collaborative environment, we strive to make deep learning more accessible and manageable for everyone involved. Users can either create a neural network from the ground up or explore our extensive library filled with standard network components, architectures, cutting-edge research, and pre-trained models, allowing for personalized experimentation and development. With just one click, you can construct your neural network while gaining a clear visual representation and interaction capabilities with each component. Additionally, effortlessly adjust hyperparameters like epochs, features, and labels to refine your model, ensuring a tailored experience that enhances your understanding of neural networks. This platform not only simplifies the technical aspects but also encourages creativity and innovation in AI development.
Description
You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.
API Access
Has API
API Access
Has API
Integrations
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Azure Kubernetes Service (AKS)
Dask
Feast
Flyte
Google Cloud Platform
Integrations
Amazon EC2 Trn2 Instances
Amazon EKS
Amazon SageMaker
Amazon Web Services (AWS)
Anyscale
Azure Kubernetes Service (AKS)
Dask
Feast
Flyte
Google Cloud Platform
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Neuralhub
Website
neuralhub.ai/
Vendor Details
Company Name
Anyscale
Founded
2019
Country
United States
Website
ray.io
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization