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1 Ratings
30 Ratings
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Score 10 out of 100
30 Ratings
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Score 8.1 out of 100

Likelihood to Recommend

Kortical

Kortical is really widely applicable to many use cases, although it doesn't handle images or video it is great to help you build really great ML models without needing to plan ahead what you are going to try, you let the platform build you the best model. It is suited to beginner and more advanced data scientists as you can edit the code to narrow the search space which makes model creation more you build it without AutoML. Hosting the model behind an API that is ready to go is great as it saves so much time vs doing that dev work from scratch
Anonymous | TrustRadius Reviewer

TensorFlow

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 networks2. 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).
Anonymous | TrustRadius Reviewer

Pros

Kortical

  • The NLP models results were much better than the ones that we did outside of the platform.
  • It is really easy and quick to build a good model with a lot of the manual boring tasks all done automatically like one hot encoding, etc.
  • Kortical shows the features and their importance for any model type as part of the platform which is great for understanding the models.
Anonymous | TrustRadius Reviewer

TensorFlow

  • 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.
Nitin Pasumarthy | TrustRadius Reviewer

Cons

Kortical

  • It would be ideal to have Jupyter built into the platform, they say it is coming.
  • Also while it is easy to use, at the start it would have been helpful to have more help guides.
Anonymous | TrustRadius Reviewer

TensorFlow

  • 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.
Nisha murthy | TrustRadius Reviewer

Usability

Kortical

No score
No answers yet
No answers on this topic

TensorFlow

TensorFlow 9.0
Based on 1 answer
Support of multiple components and ease of development.
Anupam Mittal | TrustRadius Reviewer

Support Rating

Kortical

Kortical 9.0
Based on 1 answer
Their support is great as we use Slack and we have our own channel and they always respond really quickly. Data Science support is available to help unblock you as well as dev support as we're setting up the data feeds. It would be great if there were more FAQ or self-help guides in the platform but the personal touch is also really appreciated and probably gets us there quicker anyway.
Anonymous | TrustRadius Reviewer

TensorFlow

TensorFlow 9.3
Based on 2 answers
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.
Anonymous | TrustRadius Reviewer

Implementation Rating

Kortical

No score
No answers yet
No answers on this topic

TensorFlow

TensorFlow 8.0
Based on 1 answer
Use of cloud for better execution power is recommended.
Anupam Mittal | TrustRadius Reviewer

Alternatives Considered

Kortical

No answers on this topic

TensorFlow

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
Anonymous | TrustRadius Reviewer

Return on Investment

Kortical

  • ROI is great as what we would spend on compute we get the AutoML for essentially the same price so it is cost neutral as Kortical comes with compute built-in.
  • The results mean that we can automate so much more than our previous model so that is key to the positive ROI.
  • The platform auto trains new models and lets us know when there is a better model so it has saved a lot of time so we can focus on new business problems to solve with ML.
Anonymous | TrustRadius Reviewer

TensorFlow

  • 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.
Shambhavi Jha | TrustRadius Reviewer

Screenshots

Pricing Details

Kortical

General

Free Trial
Yes
Free/Freemium Version
Premium Consulting/Integration Services
Yes
Entry-level set up fee?
No

TensorFlow

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

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