Amazing new features coming in the new release of Deep Learning Studio by Deep Cognition. Do you have a deep learning model but you want it in TensorFlow or MXNet? now you can convert it! JupyterLab preconfigured for you, H2O is now available as pre-configured environment and new integration features with Talend!

Deep Learning is fun and amazing. Nowadays is very easy to do deep learning, you have lot’s of great frameworks and libraries, platforms and much more. But I think that the one changing the game here is Deep Cognition.
With their new release they added amazing features to their Deep Learning Studio (DLS). Btw, if you want to know more about that just check this out:
To try the new features I’m going to show you you need to download the latest version of their DLS:
Improved Inter-operativity among different deep learning frameworks
Deep Learning Studio has added a feature which will let users convert the models to Tensorflow, Caffe, Keras2, MXNet, CNTK, Pytorch, or ONNX.
You can now copy the converted code and use it in favorite deep learning framework.
This is so cool because if for some reason you need to create a Pytorch code, but you only know Keras, now you can transform your code very easily.

JupyterLab is now available within Deep Learning Studio

If you haven’t heard of it, JupyterLab is the next-generation user interface for Project Jupyter. It offers all the familiar building blocks of the classic Jupyter Notebook (notebook, terminal, text editor, file browser, rich outputs, etc.) in a flexible and powerful user inteface that can be extended through third party extensions.
JupyterLab is an interactive development environment for working with notebooks, code and data. Most importantly, JupyterLab has full support for Jupyter notebooks.
JupyterLab provides a high level of integration between notebooks, documents, and activities:
- Drag-and-drop to reorder notebook cells and copy them between notebooks.
- Run code blocks interactively from text files (.py, .R, .md, .tex, etc.).
- Link a code console to a notebook kernel to explore code interactively without cluttering up the notebook with temporary scratch work.
- Edit popular file formats with live preview, such as Markdown, JSON, CSV, Vega, VegaLite, and more.
JupyterLab is built on top of an extension system that enables you to customize and enhance JupyterLab by installing additional extensions.
And now is there for you inside of DLS:

H2O.ai is now available as pre-configured environment in DLS

And yes! The last picture of JupyterLab was a teaser for H2O! Now is part of DLS as well.
H2O is open-source software for big-data analysis. It is produced by the company H2O.ai.

If you want to see how to use H2O to change your life as a Data Scientist I recommend you take a look at Matthew Dancho‘s course on Data Science For Business With R (you can use a this coupon code for 15% off!):
And finally!
Talend Open Studio is now available within Deep Learning Studio

Talend Open Studio delivers a single platform for data integration across public, private, and hybrid cloud, as well as on-premises environments.
With Talend you have:
- Powerful, easy-to-use features. Talend Open Studio for Data Integration, which you can download and use at no cost, provides all the functionality you need to design and execute a wide range of data integration processes such as data migration (including both ETL and ELT) and data synchronization. With an Eclipse-based graphical development environment, more than 900 components and built-in data connectors, a unified metadata repository, automated generation of Java code, and robust ETL testing functionality, subscription-based Talend Data Integration supplements Talend Open Studio for Data Integration with functionality specifically designed for enterprise-scale projects, such as team collaboration tools, industrial-scale deployment, and real-time load balancing.
- Proven performance. Launched in 2006, Talend Open Studio for Data Integration has rapidly gained market share, with millions of downloads and hundreds of thousands of users. Subscribers to the enterprise version of Talend’s data integration platform number in the thousands and include some of the largest corporations in the world.
- Big cost savings. Talend’s open source solutions deliver substantial cost savings compared to either labor-intensive custom development or proprietary software. The savings associated with the no-charge Talend Open Studio for Data Integration are obvious, but even with subscription-based Talend Data Integration, costs are markedly lower than with proprietary technologies.
- Active community. The community around Talend’s Data integration and application integration solutions is extremely active. Several community applications are available for sharing questions, advice, and code.
- Backing by Talend. Talend applies a major and ongoing R&D; effort to the maintenance and improvement of its open source products. The vendor provides professional quality user documentation and training materials, and for those who want it, first-rate technical support and professional services.
And now is integrated into DLS, like a Open Studio ETL. A must if you want to improve your data integration workflows.

I really think GUIs and AutoML are the near future of getting things done with Deep Learning. Don’t get me wrong, I love coding, but I think the amount of code we will be writing next years will decay.
We cannot spend so many hours worldwide programming the same stuff over and over again, so I think these two features (GUIs and AutoML) will help Data Scientist on getting more productive and solving more problems.
Download the new DLS, check this new features and share it with others!
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