Likelihood to Recommend The machine learning modeling and time-series forecasting are the best things that Neuton's platform provides. Researchers in the field of healthcare, marketing and various other industries can use this platform to get more in-depth insights into the dataset that they have been working on. Neuton.ai is going to bring in image detection and text analysis in the future which makes the perfect choice for people from product management profiles and various Data Science backgrounds.
Read full review TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
Read full review Pros Exploratory Data Analysis Machine learning modeling Time Series forecasting Read full review A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc. Amazing community helps developers obtain knowledge faster and get unblocked in this active development space. Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models. Read full review Cons User Onboarding with Google cloud platform is the most confusing part, this can be definitely be improved UI of the platform Front end of the website seems simple, little more features can be added so that people or users can navigate to various pages and know more about the platform Read full review RNNs are still a bit lacking, compared to Theano. Cannot handle sequence inputs Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time. Read full review Usability Support of multiple components and ease of development.
Read full review Support Rating Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
Read full review Implementation Rating Use of cloud for better execution power is recommended.
Read full review Alternatives Considered Read full review Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features,
Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
Read full review Return on Investment We have had 2% increase in our market reach using the EDA from the Neuton's Platform Read full review Learning is s bit difficult takes lot of time. Developing or implementing the whole neural network is time consuming with this, as you have to write everything. Once you have learned this, it make your job very easy of getting the good result. Read full review ScreenShots