ConvNetJS Reviews & Product Details

I like about ConvNetJS that it has a very strong selling point. It brings software facing hardware issues down. No installations of the software required, no expensive GPUs required, just open a tab and start training. This lowers the barrier to entry for learning because it does not require a high setup for the beginners and hobbyists who are likely interested in some light experimenting with deep learning. Review collected by and hosted on G2.com.

The ConvNetJS on the other hand can be quite demanding on the resource side of your computer. Educating the even robust models can be extremely time-consuming on average municipal computers. The library has an issue of being a little bit behind more advanced features found in other deep learning frameworks and this can be a disadvantage for judgment of its suitability for professional applications. Review collected by and hosted on G2.com.

- ConvNetJS provides a simple API for creating and training neural network models.

- we dont have to care about the dependency error is great thing for us

- This labrary is available in javascript as well as NodeJs Which make to more flexible whether to use in frontend or backend

- Easy to integrate

- And flexiable dont relay on specific type of browser Review collected by and hosted on G2.com.

I found That debuging it take lot of time as less avaibility of resources

Image cliffication model take little time at frontend Review collected by and hosted on G2.com.

I find ConvNetJS to be an unstable javascript library, of any errors and bugs. Its compatibility, with the browser versions is not impressive. There are some issues with Microsoft Edge. It is a tool with low potential and beginners find it difficult due to its difficulty. Review collected by and hosted on G2.com.

ConvNetJS lacks documentation and beginner friendly support. The learning curve is steep for individuals to JavaScript libraries making it difficult to fully harness its potential. Review collected by and hosted on G2.com.

There are problems with it as a tool. It is unable to integrate with Chrome making it unfamiliar and less user friendly. I have come across many glitches or problems. The processing speed is a bit slow. Review collected by and hosted on G2.com.

It is not widely used. ConvNetJS needs to benefit from documentation and tutorials tailored for beginners to help them grasp its functionality easily. ConvNetJS has not solved the problem of implementing deep learning algorithms. Review collected by and hosted on G2.com.

With the combination of Java script this one of the best experience provides.common neauralnetwork module which provide the great support and experience. With the help of tutorial things are much

Easier. Review collected by and hosted on G2.com.

This app is more familiar with chrome.

I want other app to also get same experience.

Some time things are not that much clear but it gives the relevant results. Review collected by and hosted on G2.com.

This library is simply awesome as it allows us to train models directly through browsers and we don't have to worry about installation of anything. Review collected by and hosted on G2.com.

Nothing as of now. I have been working with ConvNetJs for last few months to understand how this works and I found it really interesting till now. Review collected by and hosted on G2.com.

It has such very sufficient features which makes easy deep learning models. As it is JavaScript library also it is a open source. Review collected by and hosted on G2.com.

To be honest nothing is there to dislike ConvNetJS, Review collected by and hosted on G2.com.

ConvNetJS is a library built from Javascript that enables users to train Deep Learning models implemented as Neural Networks when loaded into a web browser. It is an experimental reinforcement learning module derived from Deep Q Learning and can reach its full potential without additional compilers, programs, graphics processing units (GPUs), or configurations. The source code is published under the MIT License on GitHub, where multiple AI groups collaborate to improve this deep learning tool. ConvNetJS trains and specifies AI-based convolutional networks for image processing. Review collected by and hosted on G2.com.

Despite its many benefits, ConvNetJS can be challenging for novices to master. It has a slow processing time, which is a con, but if you've used it, you should stick with it. It should receive a more significant amount of praise than it does. Review collected by and hosted on G2.com.

As a frontend engineer, this library is a saver to train models using javascript or node js.

We have been using this to train models' best work at the frontend side, with no dependency on the server-side application.

A quick way to train the model.

Easy to integrate and less time to bootstrap.

It gives the flexibility to execute the training model in a choice of browser, we have done it using Chrome. Review collected by and hosted on G2.com.

Sometimes it takes time to load on the browser, which can be improved. Mostly works or is compatible with all the latest versions of the browser but. I faced an issue while loading it on Microsoft edge.

At times faced challenges on the documentation side; not every junior team member could understand the documentation and start building. Strong work can be done to improve community support or documentation.

Debugging is also a challenge we have faced; we did find any easy way to do it. Review collected by and hosted on G2.com.

There is no need to install any additional application to run it or compile it, not even a developer tool you need to code for Deep Learning neural networks Review collected by and hosted on G2.com.

Since it is not widely used hence sometimes it is difficult to search for a solution over internet Review collected by and hosted on G2.com.