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What is Keepsake?

Keepsake is an open-source Python library tailored for overseeing version control within machine learning experiments and models. It empowers users to effortlessly track vital elements such as code, hyperparameters, training datasets, model weights, performance metrics, and Python dependencies, thereby facilitating thorough documentation and reproducibility throughout the machine learning lifecycle. With minimal modifications to existing code, Keepsake seamlessly integrates into current workflows, allowing practitioners to continue their standard training processes while it takes care of archiving code and model weights to cloud storage options like Amazon S3 or Google Cloud Storage. This feature simplifies the retrieval of code and weights from earlier checkpoints, proving to be advantageous for model re-training or deployment. Additionally, Keepsake supports a diverse array of machine learning frameworks including TensorFlow, PyTorch, scikit-learn, and XGBoost, which aids in the efficient management of files and dictionaries. Beyond these functionalities, it offers tools for comparing experiments, enabling users to evaluate differences in parameters, metrics, and dependencies across various trials, which significantly enhances the analysis and optimization of their machine learning endeavors. Ultimately, Keepsake not only streamlines the experimentation process but also positions practitioners to effectively manage and adapt their machine learning workflows in an ever-evolving landscape. By fostering better organization and accessibility, Keepsake enhances the overall productivity and effectiveness of machine learning projects.

What is FeedStock Cortex?

Cortex leverages advanced machine learning capabilities to seamlessly oversee research engagements and identify research incentives across various communication platforms. Our service offers the most streamlined and discreet research payment validation, ensuring that your organization remains compliant and functionally effective while relying on precise data for strategic decision-making. Functioning in real-time, Cortex automatically collects, analyzes, and securely understands all research interactions, both internal and external, within your organization's information flow. This groundbreaking system alleviates the burden of monitoring these interactions internally and eliminates the need to rely on and reconcile sell-side data, enabling your investment professionals to focus on their primary areas of expertise. Ultimately, Cortex enhances your team's operational efficiency and effectiveness, fundamentally changing the way research interactions are handled. By integrating Cortex into your processes, you can expect a significant improvement in collaboration and insight generation across your organization.

Media

Media

Integrations Supported

Amazon S3
Google Cloud Storage
JSON
PyTorch
Python
TensorFlow
scikit-learn

Integrations Supported

Amazon S3
Google Cloud Storage
JSON
PyTorch
Python
TensorFlow
scikit-learn

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Replicate

Company Location

United States

Company Website

keepsake.ai/

Company Facts

Organization Name

FeedStock

Date Founded

2015

Company Location

United Kingdom

Company Website

feedstock.com/products/cortex/

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Version Control

Branch Creation / Deletion
Centralized Version History
Code Review
Code Version Management
Collaboration Tools
Compare / Merge Branches
Digital Asset / Binary File Storage
Isolated Code Branches
Option to Revert to Previous
Pull Requests
Roles / Permissions

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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