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features
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support

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Description

Manage and optimize models throughout the entire ML lifecycle. This includes experiment tracking, monitoring production models, and more. The platform was designed to meet the demands of large enterprise teams that deploy ML at scale. It supports any deployment strategy, whether it is private cloud, hybrid, or on-premise servers. Add two lines of code into your notebook or script to start tracking your experiments. It works with any machine-learning library and for any task. To understand differences in model performance, you can easily compare code, hyperparameters and metrics. Monitor your models from training to production. You can get alerts when something is wrong and debug your model to fix it. You can increase productivity, collaboration, visibility, and visibility among data scientists, data science groups, and even business stakeholders.

Description

Models may be fleeting, but pipelines have a lasting presence. The cycle of training, evaluating, deploying, and repeating is essential. Valohai stands out as the sole MLOps platform that fully automates the entire process, from data extraction right through to model deployment. Streamline every aspect of this journey, ensuring that every model, experiment, and artifact is stored automatically. You can deploy and oversee models within a managed Kubernetes environment. Simply direct Valohai to your code and data, then initiate the process with a click. The platform autonomously launches workers, executes your experiments, and subsequently shuts down the instances, relieving you of those tasks. You can work seamlessly through notebooks, scripts, or collaborative git projects using any programming language or framework you prefer. The possibilities for expansion are limitless, thanks to our open API. Each experiment is tracked automatically, allowing for easy tracing from inference back to the original data used for training, ensuring full auditability and shareability of your work. This makes it easier than ever to collaborate and innovate effectively.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Microsoft Azure Yes 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
Apache Spark Yes 
Axolotl Yes 
Clone Protocol Yes 
CogniSync Yes 
Flask Yes 
Google Cloud Platform Yes 
New Relic Yes 
Plotly Dash Yes 
PyTorch Yes 
Python Yes 
ScalePad Backup Radar Yes 
Seldon Yes 
TensorFlow Yes 
Ultralytics Yes 
WEKA No 
Weaviate Yes 
ZenML Yes 

Integrations

Microsoft Azure Yes 
Amazon SageMaker No 
Amazon Web Services (AWS) No 
Apache Spark No 
Axolotl No 
Clone Protocol No 
CogniSync No 
Flask No 
Google Cloud Platform No 
New Relic No 
Plotly Dash No 
PyTorch No 
Python No 
ScalePad Backup Radar No 
Seldon No 
TensorFlow No 
Ultralytics No 
WEKA Yes 
Weaviate No 
ZenML No 

Pricing Details

$179 per user per month
Free Trial No 
Free Version Yes 

Pricing Details

$560 per month
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 No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Comet

Founded

2017

Country

United States

Website

www.comet.com

Vendor Details

Company Name

Valohai

Founded

2016

Country

Finland

Website

valohai.com

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Deep Learning

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

Machine Learning

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

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics Yes 
Process/Workflow Automation Yes 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Deep Learning

Convolutional Neural Networks Yes 
Document Classification Yes 
Image Segmentation Yes 
ML Algorithm Library Yes 
Model Training Yes 
Neural Network Modeling Yes 
Self-Learning Yes 
Visualization Yes 

Machine Learning

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

Predictive Analytics

AI / Machine Learning Yes 
Benchmarking Yes 
Data Blending No 
Data Mining No 
Demand Forecasting Yes 
For Education No 
For Healthcare No 
Modeling & Simulation Yes 
Sentiment Analysis No 

Alternatives

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