Top Rated Caffe Alternatives
This software is easy to use. Also helps with creativity and cost when building a menu and staying under costs. Wide library of items to choose from. Review collected by and hosted on G2.com.
The ability to customize, some options are prefixed and it is a few extra steps when customizing menu/recipes Review collected by and hosted on G2.com.
15 out of 16 Total Reviews for Caffe
The upsides of using Caffe are its speed, flexibility, and scalability. It’s incredibly fast and efficient, allowing you to quickly design, train, and deploy deep neural networks. It provides a wide range of useful tools and libraries, making it easier to create complex models and to customize existing ones. Finally, Caffe is very scalable, allowing you to easily scale up your models to large datasets or to multiple machines, making it an ideal choice for distributed training. Review collected by and hosted on G2.com.
Caffe has been around for a while and is not as efficient as some of the newer frameworks such as TensorFlow, PyTorch, and MXNet. Caffe also lacks some features and flexibility compared to newer frameworks, and the documentation can be limited and hard to understand. Additionally, Caffe is not optimized for mobile devices, so it can be difficult to deploy models to mobile devices. Finally, Caffe can be difficult to debug when errors occur. Review collected by and hosted on G2.com.
One of the best machine learning software where you can use your most time for work and easy purpose use. osam frame works and osam algorithms works so nicely that you feel to be comfortable with the software ..writing code is not nesaccary for classification or other tasks ..Osam feature is that it runs on GPU and NoN GPU based system.. Review collected by and hosted on G2.com.
Dislike is that it's not easy to install on the anaconda software little tough to handle ..not more dislike is there ..so we can not comment more that it is bad due to any reason . Review collected by and hosted on G2.com.
I have been working on machine learning and caffe has been one of the software I use the most. It has eased my task on image classification and has good frameworks for using algorithm like CNN RNN and many others Review collected by and hosted on G2.com.
Being in research department and doing more of deep learning work on images , I would require openCL which is still need to add more features. So I need to switch to other software for that some. Would be better if it has openCl features added. Review collected by and hosted on G2.com.
This is incredibly quick and supports GPU pretty well, to start. There is a tonne of built-in code, thus writing code is not necessary for classification or other tasks. supports data types comparable to those in Python. Review collected by and hosted on G2.com.
Caffe was created to just focus on visuals, ignoring supporting elements like text, sound, and timing. It follows that Caffe supports convolutional neural networks well, but not well enough to support time-sequence RNN or LSTM. Additionally, the Layers-based design pattern is not RNN-friendly. Review collected by and hosted on G2.com.
It run on both GPU based system and non-GPU based system Review collected by and hosted on G2.com.
It isn't easy to install on anaconda software.It is difficult to do in comparison to other library like numpy. Review collected by and hosted on G2.com.
What's most helpful with the tool is its usability and easy-to-use interface. It's also helpful in scaling up industrial applications, academic research, and even making start-up prototypes. Review collected by and hosted on G2.com.
So far, i have not experienced any pain points for the period I have been using the tool. Everything works perfectly. Review collected by and hosted on G2.com.
Machine learning and Data mining programs to understand and learn the technologies quickly. It is a great application, as it makes things organised and thus easier to learn and understand. Review collected by and hosted on G2.com.
Nothing as such to dislike about it. I love it. Review collected by and hosted on G2.com.
Easy to configure, and as it has inbuild features which is a handy thing for a noncoding background people Review collected by and hosted on G2.com.
As of now I don't dislike anything as it serves it purpose Review collected by and hosted on G2.com.
Caffe supports deep learning framework that is easy to understand & we don't need to write much code & it supports configured neural networks structures so we don't need to write much code. Review collected by and hosted on G2.com.
Some problems which is lack of good support of time sequence RNN etc. Review collected by and hosted on G2.com.
Unlike some of its competitors the learning curve for Caffe is relatively small due to its simple user interface. Review collected by and hosted on G2.com.
It can be difficult to implement some changes, such as introducing new layers or changing the base library. Review collected by and hosted on G2.com.
