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49 packages found
Helper functions to use tensorflow in nodejs for transfer learning, image classification, and more
- tensorflow
- tensorflowjs
- tfjs
- typescript
- helpers
- utility
- image
- embedding
- classifier
- neural-network
- transfer-learning
- deep-learning
- feature-extraction
Maintenance: 33%. Quality: 60%. Popularity: 2%.
Simple to use neural network implementation in pure TypeScript with GPU support.
- ml
- machine-learning
- deep-learning
- neural-network
- neural-network-engine
- gan
- generative-adversarial-network
- artificial-intelligence
- classification
- regression
- image-processing
- unsupervised-learning
- supervised-learning
- vae
Maintenance: 32%. Quality: 61%. Popularity: 2%.
Image augmentation library and cli for machine learning tasks
- image
- augment
- augmentation
- machine-learning
- deep-learning
- image-processing
- cli
- typescript
- sharp
- image-manipulation
- data-augmentation
- image-augmentation
- rotate
- scale
- View more
Maintenance: 33%. Quality: 61%. Popularity: 1%.
The very first AGI library has core functionalities to help you to generate your Personalized Artificial General Intelligence.
- common
- core
- ai
- artificial-intelligence
- agi
- gpt-4
- openai
- microsoft
- personalized-agi
- machine-learning
- deep-learning
- role-based-agi
- first agi
- pi agi
- View more
Maintenance: 32%. Quality: 61%. Popularity: 0%.
Integrates OpenAI's API into web applications, offering easy access to AI-driven features via a JavaScript object interface and HTML5 attributes.
- openai
- cocreate
- low-code-framework
- ai-integration
- web-applications
- javascript-api
- html5-attributes
- ai-driven-features
- machine-learning
- natural-language-processing
- image-generation
- deep-learning
- cocreate-framework
- html5-framework
Maintenance: 33%. Quality: 54%. Popularity: 2%.
Run modern deep learning models in the browser.
Maintenance: 33%. Quality: 54%. Popularity: 1%.
WebNN API polyfill
Maintenance: 32%. Quality: 53%. Popularity: 2%.
A TypeScript library for advanced usage of OpenAI APIs.
Maintenance: 33%. Quality: 53%. Popularity: 0%.
Run modern deep learning models in Node.js.
Maintenance: 32%. Quality: 54%. Popularity: 1%.
This will allow users of your npm package to generate images or ask questions through the `FreeAI` class, keeping both functionalities in one package.
- free
- ai
- image
- generation
- chatgpt
- api
- fun
- random
- free-ai
- ai-image
- AI-generation
- AI-image
- machine-learning
- AI-chat
- View more
Maintenance: 33%. Quality: 51%. Popularity: 1%.
DeepDetect JS client
Maintenance: 22%. Quality: 63%. Popularity: 0%.
A JavaScript library like PyTorch, built from scratch.
Maintenance: 33%. Quality: 45%. Popularity: 0%.
Javascript image annotate, use in deep learning
Maintenance: 33%. Quality: 41%. Popularity: 0%.
JavaScript AI engine Focused on simplicity of use.
Maintenance: 29%. Quality: 42%. Popularity: 0%.
A small deep-learning library to distinguish human and bot from their mouse movements.
Maintenance: 22%. Quality: 48%. Popularity: 0%.
Here is a README generated from the code snippet:
- vectorizer
- machine-learning
- code-vectorization
- embedding
- ai
- artificial-intelligence
- nlp
- natural-language-processing
- code-embedding
- programming
- code-processing
- software-engineering
- tokenizer
- code-tokenizer
- View more
Maintenance: 15%. Quality: 54%. Popularity: 0%.
A small deep-learning library to distinguish human and bot from their mouse movements.
Maintenance: 20%. Quality: 48%. Popularity: 0%.
TypeScript/Node.js library enabling seamless integration of GPT-4 and GPT-3.5 models with Azure and OpenAI. This toolkit offers user-friendly interfaces, simplifying AI model utilization in your applications.
- common
- core
- ai
- artificial-intelligence
- agi
- gpt-4
- gpt-3.5
- openai
- microsoft
- azure
- personalized-agi
- machine-learning
- deep-learning
- role-based-agi
- View more
Maintenance: 6%. Quality: 61%. Popularity: 0%.
Unleash the ⚡️GPU power⚡️ for [mind-net.js](https://www.npmjs.com/package/mind-net.js).
Maintenance: 15%. Quality: 51%. Popularity: 0%.
A web-first, cross-platform ML framework.
Maintenance: 31%. Quality: 33%. Popularity: 0%.