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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
PhotoVCarve rapidly transforms photographs and images into precise toolpaths, compatible with nearly all CNC routing and engraving machines. It's an excellent choice for crafting 3D lithophanes from photographs, which serve as beautiful gifts, cherished keepsakes, and lasting mementos. The software produces grooves of varying widths and depths to capture the intricate details of the original image. The quality of the outcome heavily relies on a strong contrast between the surface material and the machined details. In darker regions of a photograph, PhotoVCarve creates wider grooves, while lighter sections are rendered with narrower ones. The toolpaths are calculated automatically based on the selected cutter, ensuring optimal results. Lithophanes, which are 3D impressions, appear somewhat flat and unremarkable under regular lighting; however, when illuminated from behind, they reveal breathtaking 3D images filled with depth and intricate detail, making them truly captivating. This combination of technology and artistry makes PhotoVCarve a valuable tool for creatives looking to bring photographs to life.
API Access
Has API
API Access
Has API
Integrations
Amazon S3
Google Cloud Storage
JSON
PyTorch
Python
TensorFlow
VCarve
scikit-learn
Integrations
Amazon S3
Google Cloud Storage
JSON
PyTorch
Python
TensorFlow
VCarve
scikit-learn
Pricing Details
Free
Free Trial
Free Version
Pricing Details
$6.21 per month
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
Replicate
Country
United States
Website
keepsake.ai/
Vendor Details
Company Name
Vectric
Country
United Kingdom
Website
www.vectric.com/products/photovcarve/
Product 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
Product Features
Engineering
2D Drawing
3D Modeling
Chemical Engineering
Civil Engineering
Collaboration
Design Analysis
Design Export
Document Management
Electrical Engineering
Mechanical Engineering
Mechatronics
Presentation Tools
Structural Engineering