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ease
features
design
support

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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

Thanks is an all-encompassing platform for employee recognition that streamlines the process of celebrating both significant milestones and everyday accomplishments, making it efficient and straightforward. It automates the recognition of years of service by providing meaningful awards and digital keepsakes on anniversaries, while also offering timely automated greetings for birthdays and work-related milestones. The platform’s Nominate feature empowers both managers and colleagues to create performance and incentive awards, which can include a wide array of options such as travel experiences, vouchers, and branded merchandise through a vast global rewards network. Additionally, Custom Awards facilitate personalized gifting with access to over 9,000 carefully selected experiences, and the Memories feature gathers recognition messages and photos into digital keepsakes delivered on service anniversaries. This daily peer-to-peer Thanks function operates within a social platform to nurture a culture of appreciation that resonates with company values, and the integrated gamification elements enhance engagement by encouraging healthy competition among employees. Ultimately, Thanks not only recognizes achievements but also fosters a positive workplace atmosphere.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

BambooHR
Gmail
Google Chrome
Google Cloud Storage
Google Workspace
JSON
Microsoft Azure
Microsoft Outlook
Microsoft Viva Engage
Mozilla Firefox
Okta
OneLogin
PyTorch
Python
SAP SuccessFactors
Slack
TensorFlow
WhatsApp
Workday HCM
scikit-learn

Integrations

BambooHR
Gmail
Google Chrome
Google Cloud Storage
Google Workspace
JSON
Microsoft Azure
Microsoft Outlook
Microsoft Viva Engage
Mozilla Firefox
Okta
OneLogin
PyTorch
Python
SAP SuccessFactors
Slack
TensorFlow
WhatsApp
Workday HCM
scikit-learn

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
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

Thanks

Founded

2019

Country

United States

Website

www.thanks.com

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

Employee Recognition

Goals
Leaderboards / Activity Tracking
Manager-to-Peer Recognition
Mention Management
Nominations
Peer-to-Peer Recognition
Performance Management
Rewards Catalog
Rewards Points
Social Recognition
eCards

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