- 1 Introduction
- 6 Conclusion
Its GitHub repository has 1.3k stars and is undergoing active development.
Since it supports real-time classification, it can also be used in chatbots for natural language understanding. With over 1K stars its Github repository is still active and surely worth checking.
It offers the following interesting pre-trained models –
- Image Classification
- Object Detection
- Body Segmentation
- Pose Estimation
- Text Toxicity Detection
- Universal Sentence Encoder
- Speech Command Recognition
- KNN Classifier
- Simple Face Detection
- Semantic Segmentation
- Face Landmark Detection
- Hand Pose Detection
- Natural Language Question Answering
It is an open-source project on GitHub with 14.8K stars and is under continuous development and maintenance.
- Feedforward Neural Network (with and without GPU)
- Recurrent Neural Network
- Long Short Term Memory
Interestingly, its original creator Harthur had abandoned the GitHub project a few years back in spite of gaining initial popularity. This project now continues in a separate Github repository with more than 11K stars and is actively maintained by a large community.
It works by compressing the model for faster execution in the browser. Its GitHub repository has 1.8K and the last active release happened in January 2020.
- Regular Neural Network Models
- Convolutional Neural Network
- Deep Q Learning (Reinforcement Learning)
The demos hosted in the repository are quite cool but in spite of more than 10K stars its GitHub is no longer maintained by its creator Karpathy. And unfortunately, there is no community support either resulting in no updates for many years now.
- Multilayer Perceptron
- Multilayer LSTMS
- Liquid State Machines
- Hopfield Networks
It also provides a trainer module that is capable of training any given neural network architecture.
The creator of this library is Juan Cazala and its GitHub repository has 6.5K stars but it has not seen much activity in the last couple of years.
Since it is a high-level abstraction library ML5.js takes care of all the heavy lifting of memory management and GPU acceleration behind the scene and you need not do anything.
It comes with many pre-trained models for detecting human poses, generating text, styling an image with another, composing music, pitch detection, and common English language word relationships, etc
Apart from this, using ML5.js you can also create and train your own neural network model in the browser and it also extends support for Transfer Learning. And to add more variety to its offering it also supports algorithms for KMeans Clustering and KNN-Classification.
This high-level library is perfect for those people who are afraid to get entangled in the low-level complexities of Tensorflow.js but you should be aware that it does not support node.js at the moment.
This library only lets you inference pre-trained models and you will not be able to train your own models.
The library was created by Steven Miller and the GitHub repository has got over 1.4K stars but unfortunately has not seen activity in development in the last four years.
Although you can create and train your own neural network from scratch, Neataptic comes with the following 6 pre-configured networks –
Its GitHub repository has 1K stars, however, it is no longer maintained by its author Thomas Wagenaar.
Its GitHub repository has 400+ stars but it has not seen any activity in the last 3-4 years.
Besides the core out-of-box functionality, it also offers plugin extensions for some really cool features. To give you one example, you can use the extension of .number() function to do the mathematical operation with numbers in English. Isn’t it cool?
<script> nlp.extend(compromiseNumbers) var doc = nlp('two bottles of beer') doc.numbers().minus(1) document.body.innerHTML = doc.text() // 'one bottle of beer' </script>
The library was has been created by Spencer Kelly and its Github repository which has almost 10K stars is still actively maintained by himself and a handful of contributors.
Neuro.js is also compatible with both browser execution and node.js making it a good option.
Its Github repository has more than 9k stars and more than 120 contributors that have added support for other languages apart from English like Spanish, Russian, etc.
- Image processing
- Object detection
- Features framework
- Image codecs
The popularity of tracking.js can be attributed to the fact that its GitHub repository has 8.7k stars, however, it has not seen much development in recent years and they are looking for maintainers for the repository.
WebGazer.js can help track user’s attention on the website and provide user experience accordingly. Its real-time gaze prediction is compatible with all major browsers.
With close to 3K stars its GitHub repository is quite popular and is still actively maintained.
Its Github repository has got 12K stars and is still somewhat actively maintained by its creator Vincent and other contributors.