Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
AppGet is an open-source package manager moderated by GitHub that emphasizes security, automation, and user-friendliness. All moderation processes are conducted through GitHub, allowing anyone to submit a pull request that is subsequently reviewed and approved by our dedicated team. Users can install, update, and remove any application found in our library, even those not initially installed via AppGet. Both our client code and application library are fully open-source and accessible on GitHub. Our AppGet bots tirelessly operate around the clock to ensure our application library remains current with the latest software versions. Applications listed in AppGet's library are always sourced directly from the original authors, eliminating the hassle of searching the internet for download links. Furthermore, AppGet employs metadata-only manifest files, streamlining the review process for manifests and enhancing overall security. This approach not only simplifies the workflow for users but also fosters a trustworthy environment for software management.
Description
ConvNetJS is a JavaScript library designed for training deep learning models, specifically neural networks, directly in your web browser. With just a simple tab open, you can start the training process without needing any software installations, compilers, or even GPUs—it's that hassle-free. The library enables users to create and implement neural networks using JavaScript and was initially developed by @karpathy, but it has since been enhanced through community contributions, which are greatly encouraged. For those who want a quick and easy way to access the library without delving into development, you can download the minified version via the link to convnet-min.js. Alternatively, you can opt to get the latest version from GitHub, where the file you'll likely want is build/convnet-min.js, which includes the complete library. To get started, simply create a basic index.html file in a designated folder and place build/convnet-min.js in the same directory to begin experimenting with deep learning in your browser. This approach allows anyone, regardless of their technical background, to engage with neural networks effortlessly.
API Access
Has API
No
API Access
Has API
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
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)
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)
No
In Person
No
Vendor Details
Company Name
AppGet
Country
Canada
Website
appget.net
Vendor Details
Company Name
ConvNetJS
Website
cs.stanford.edu/people/karpathy/convnetjs/
Product Features
Product Features
Deep Learning
Convolutional Neural Networks
No
Document Classification
No
Image Segmentation
No
ML Algorithm Library
No
Model Training
No
Neural Network Modeling
No
Self-Learning
No
Visualization
No