Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Keepsake is a Python library that is open-source and specifically designed for managing version control in machine learning experiments and models. It allows users to automatically monitor various aspects such as code, hyperparameters, training datasets, model weights, performance metrics, and Python dependencies, ensuring comprehensive documentation and reproducibility of the entire machine learning process. By requiring only minimal code changes, Keepsake easily integrates into existing workflows, permitting users to maintain their usual training routines while it automatically archives code and model weights to storage solutions like Amazon S3 or Google Cloud Storage. This capability simplifies the process of retrieving code and weights from previous checkpoints, which is beneficial for re-training or deploying models. Furthermore, Keepsake is compatible with a range of machine learning frameworks, including TensorFlow, PyTorch, scikit-learn, and XGBoost, enabling efficient saving of files and dictionaries. In addition to these features, it provides tools for experiment comparison, allowing users to assess variations in parameters, metrics, and dependencies across different experiments, enhancing the overall analysis and optimization of machine learning projects. Overall, Keepsake streamlines the experimentation process, making it easier for practitioners to manage and evolve their machine learning workflows effectively.
Description
The process of developing a model is inherently iterative, often spanning weeks, months, or even years, and it involves challenges such as reproducing results, maintaining version control, and auditing previous work. It is important to document each phase of model building, as well as the reasoning behind decisions made along the way. Rather than being a secretive file stored away, a model should serve as a clear and accessible resource for all stakeholders to monitor and evaluate consistently. Prevision.io facilitates this by enabling you to log every experiment during training, capturing its attributes, automated analyses, and various versions as your project evolves, regardless of whether you utilize our AutoML or your own methodologies. You can effortlessly experiment with a multitude of feature engineering techniques and algorithm options to create models that perform exceptionally well. With just a single command, the system can explore different feature engineering methods tailored to various data types, such as tabular data, text, or images, ensuring that you extract the maximum value from your datasets while enhancing overall model performance. This comprehensive approach not only streamlines the modeling process but also fosters collaboration and transparency among team members.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon S3
Yes
Google Cloud Storage
Yes
JSON
Yes
PyTorch
Yes
Python
Yes
SkyStem ART
No
TensorFlow
Yes
scikit-learn
Yes
Integrations
Amazon S3
No
Google Cloud Storage
No
JSON
No
PyTorch
No
Python
No
SkyStem ART
Yes
TensorFlow
No
scikit-learn
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
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
Yes
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
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Replicate
Country
United States
Website
keepsake.ai/
Vendor Details
Company Name
Prevision.io
Country
France
Website
prevision.io
Product Features
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
Version Control
Branch Creation / Deletion
No
Centralized Version History
No
Code Review
No
Code Version Management
No
Collaboration Tools
No
Compare / Merge Branches
No
Digital Asset / Binary File Storage
No
Isolated Code Branches
No
Option to Revert to Previous
No
Pull Requests
No
Roles / Permissions
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
Yes
Statistical / Mathematical Tools
Yes
Templates
No
Visualization
No