Dato GraphLab – Ep. 15 (Deep Learning SIMPLIFIED)
Dato GraphLab is a good software platform for Deep Learning projects that require graph analytics and other important algorithms. It provides two deep nets, sophisticated data munging, an intuitive UI, and built-in enhancements for handling big data.
Deep Learning TV on
Facebook: https://www.facebook.com/DeepLearningTV/
Twitter: https://twitter.com/deeplearningtv
Dato GraphLab currently offers a vanilla MLP and a convolutional net. An important feature of the platform is the Graph Analytics toolset, which can be run alongside the deep learning models. Other provided tools include text analytics, a recommender, classification, regression, and clustering. You can also point GraphLab at multiple data sources in order to train data loads.
The platform has an intuitive UI along with an extension called the GraphLab Canvas. This extension offers highly sophisticated visualizations of your models.
Even though GraphLab needs to be deployed and maintained on your own hardware, the platform comes with many performance enhancements that speed up training on big data sets.
GraphLab offers three different types of built-in storage – tabular, columnar, and graph. In addition, the platform provides built-in GPU support which is extremely beneficial for training. You can also set up each type of model as a service that can be accessed programmatically through an API.
Under what circumstances would you use a graph in your deep learning projects? Please comment and share your thoughts.
Credits
Nickey Pickorita (YouTube art) -
https://www.upwork.com/freelancers/~0147b8991909b20fca
Isabel Descutner (Voice) -
https://www.youtube.com/user/IsabelDescutner
Dan Partynski (Copy Editing) -
https://www.linkedin.com/in/danielpartynski
Marek Scibior (Prezi creator, Illustrator) -
http://brawuroweprezentacje.pl/
Jagannath Rajagopal (Creator, Producer and Director) -
https://ca.linkedin.com/in/jagannathrajagopal
Dato GraphLab is a good software platform for Deep Learning projects that require graph analytics and other important algorithms. It provides two deep nets, sophisticated data munging, an intuitive UI, and built-in enhancements for handling big data.
Deep Learning TV on
Facebook: https://www.facebook.com/DeepLearningTV/
Twitter: https://twitter.com/deeplearningtv
Dato GraphLab currently offers a vanilla MLP and a convolutional net. An important feature of the platform is the Graph Analytics toolset, which can be run alongside the deep learning models. Other provided tools include text analytics, a recommender, classification, regression, and clustering. You can also point GraphLab at multiple data sources in order to train data loads.
The platform has an intuitive UI along with an extension called the GraphLab Canvas. This extension offers highly sophisticated visualizations of your models.
Even though GraphLab needs to be deployed and maintained on your own hardware, the platform comes with many performance enhancements that speed up training on big data sets.
GraphLab offers three different types of built-in storage – tabular, columnar, and graph. In addition, the platform provides built-in GPU support which is extremely beneficial for training. You can also set up each type of model as a service that can be accessed programmatically through an API.
Under what circumstances would you use a graph in your deep learning projects? Please comment and share your thoughts.
Credits
Nickey Pickorita (YouTube art) –
https://www.upwork.com/freelancers/~0147b8991909b20fca
Isabel Descutner (Voice) –
https://www.youtube.com/user/IsabelDescutner
Dan Partynski (Copy Editing) –
https://www.linkedin.com/in/danielpartynski
Marek Scibior (Prezi creator, Illustrator) –
http://brawuroweprezentacje.pl/
Jagannath Rajagopal (Creator, Producer and Director) –
https://ca.linkedin.com/in/jagannathrajagopal
