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features
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support

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Write a Review

Description

Guild AI serves as an open-source toolkit for tracking experiments, crafted to introduce systematic oversight into machine learning processes, thereby allowing users to enhance model creation speed and quality. By automatically documenting every facet of training sessions as distinct experiments, it promotes thorough tracking and evaluation. Users can conduct comparisons and analyses of different runs, which aids in refining their understanding and progressively enhancing their models. The toolkit also streamlines hyperparameter tuning via advanced algorithms that are executed through simple commands, doing away with the necessity for intricate trial setups. Furthermore, it facilitates the automation of workflows, which not only speeds up development but also minimizes errors while yielding quantifiable outcomes. Guild AI is versatile, functioning on all major operating systems and integrating effortlessly with pre-existing software engineering tools. In addition to this, it offers support for a range of remote storage solutions, such as Amazon S3, Google Cloud Storage, Azure Blob Storage, and SSH servers, making it a highly adaptable choice for developers. This flexibility ensures that users can tailor their workflows to fit their specific needs, further enhancing the toolkit’s utility in diverse machine learning environments.

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 Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

PyTorch Yes 
TensorFlow Yes 
Amazon EKS No 
Amazon S3 Yes 
Azure Kubernetes Service (AKS) No 
Databricks No 
Flyte No 
Google Cloud Platform No 
Google Cloud Storage Yes 
Google Kubernetes Engine (GKE) No 
HTML Yes 
Jupyter Notebook Yes 
Keras Yes 
Kubernetes No 
LaTeX Yes 
MLflow No 
MXNet Yes 
Markdown Yes 
Union Cloud No 
scikit-learn Yes 

Integrations

PyTorch Yes 
TensorFlow Yes 
Amazon EKS Yes 
Amazon S3 No 
Azure Kubernetes Service (AKS) Yes 
Databricks Yes 
Flyte Yes 
Google Cloud Platform Yes 
Google Cloud Storage No 
Google Kubernetes Engine (GKE) Yes 
HTML No 
Jupyter Notebook No 
Keras No 
Kubernetes Yes 
LaTeX No 
MLflow Yes 
MXNet No 
Markdown No 
Union Cloud Yes 
scikit-learn No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Open source. Consumption-based.
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Guild AI

Founded

2018

Country

United States

Website

guild.ai/

Vendor Details

Company Name

Anyscale

Founded

2019

Country

United States

Website

ray.io

Product Features

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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