Synaptic.js is a JavaScript library focused on neural networks and deep learning. While the provided text does not offer extensive details about features, pricing, or specific use cases, it’s evident that the library is designed to facilitate the development and training of neural networks using JavaScript.

Learning Resources and Demos:

The website offers various learning resources and interactive demos to help users understand and experiment with the library. Some of these resources include:

1. Learn XOR: XOR is a classic problem in machine learning, often used to demonstrate the capabilities of neural networks.
2. Discrete Sequence Recall: This likely pertains to training networks to recall discrete sequences, a fundamental concept in many applications.
3. Learn Image Filters: Image filtering is essential in computer vision, and the library appears to support this functionality.
4. Paint An Image: This might be a creative demonstration showing how neural networks can be used for image-related tasks.
5. Self Organizing Map: Self-organizing maps are a specific type of neural network used for clustering and visualization.
6. Read From Wikipedia: This could be an example of text processing or natural language understanding using the library.

Documentation:

1. Neurons: Explaining the core building blocks of neural networks, which are the artificial neurons.
2. Networks: Providing insights into how neural networks are structured and interconnected within the library.
3. Layers: Describing the organization of layers within neural networks, which is fundamental to their functionality.
4. Trainer: Likely detailing the training process of neural networks using Synaptic.js.
5. Architect: This section may provide guidance on designing the architecture of neural networks for specific tasks.