6 Reviews and Ratings
18 Reviews and Ratings
A well-suited scenario for using AWS Tensor Flow is when having a project with a geographically dispersed team, a client overseas and large data to use for training. AWS Tensor Flow is less appropriate when working for clients in regions where it hasn't been allowed yet for use. Since smaller clients are in regions where AWS Tensor Flow hasn't been allowed for use, and those clients traditionally don't have enough hardware, this situation deters a wider use of the tool.Incentivized
Keras is quite perfect, if the aim is to build the standard Deep Learning model, and materialize it to serve the real business use case, while it is not suitable if the purpose is for research and a lot of non-standard try out and customization are required, in that case either directly goes to low level TensorFlow API or PytorchIncentivized
Amazon Elastic Compute Cloud (EC2) allows resizable compute capacity in the cloud, providing the necessary elasticity to provide services for both, small and medium-sized businesses.Tensor Flow allows us to train our models much faster than in our on-premise equipment.Most of the pre-trained models are easy to adapt to our clients' needs.Incentivized
One of the reason to use Keras is that it is easy to use. Implementing neural network is very easy in this, with just one line of code we can add one layer in the neural network with all it's configurations.It provides lot of inbuilt thing like cov2d, conv2D, maxPooling layers. So it makes fast development as you don't need to write everything on your own. It comes with lot of data processing libraries in it like one hot encoder which also makes your development easy and fast.It also provides functionality to develop models on mobile device.Incentivized
SageMaker isn't available in all regions. This is complicated for some clients overseas.For larger instances, when using a GPU, it takes a while to talk to a customer service representative to ask for a limit increase. Given this, it's recommendable to ask in advance for a limit increase in more expensive and larger cases; otherwise, SageMaker will set the limit to zero by default.Since the data has to be stored in S3 and copied to training, it doesn't allow to test and debug locally. Therefore, we have to wait a lot to check everything after every trail.Incentivized
As it is a kind of wrapper library it won't allow you to modify everything of its backendUnlike other deep learning libraries, it lacks a pre-defined trained model to useErrors thrown are not always very useful for debugging. Sometimes it is difficult to know the root cause just with the logsIncentivized
I am giving this rating depending on my experience so far with Keras, I didn't face any issue far. I would like to recommend it to the new developers.
Keras have really good support along with the strong community over the internet. So in case you stuck, It won't so hard to get out from it.
Microsoft Azure is better than Amazon Tensor Flow because it provides easier and pre-built capabilities such as Anomaly Detection, Recommendation, and Ranking. AWS is better than IBM Watson ML Studio because it has direct and prebuilt clustering capabilities AWS, like IBM Watson ML Studio, has powerful built-in algorithms, providing a stronger platform when comparing it with MS Azure ML Services and Google ML Engine.Incentivized
Keras is good to develop deep learning models. As compared to TensorFlow, it's easy to write code in Keras. You have more power with TensorFlow but also have a high error rate because you have to configure everything by your own. And as compared to MATLAB, I will always prefer Keras as it is easy and powerful as well.Incentivized
Positive: It has allowed us to work with our overseas teams without any large hardware investing.Positive: Pre-trained models significantly reduce the time to develop solutions for our clients.Negative: Since it's a relatively new tool, you have to be careful about not paying for large errors while learning to use the tool.Incentivized
Easy and faster way to develop neural network.It would be much better if it is available in Java.It doesn't allow you to modify the internal things.Incentivized