Introduction to Skflow and TensorFlow

Below are the videos from the TensorFlow Chicago meetup—sponsored and organized by Altoros on March 1, 2016.

TensorFlow overview

In his session, Ramani Natarajan introduced the audience to TensorFlow, highlighting its major features and explaining what the tool can be used for. He also mentioned some tensor and data flow graph concepts, providing an example of how tensors can be applied in modeling.

Introduction to Skflow

Yuan Tung, Data Scientist at Uptake, provided an overview of Scikit Flow—a simplified TensorFlow interface for deep learning that allows for getting started with predictive analysis and data mining. This presentation focuses on Scikit Flow’s key features, modeling techniques, GPU and session configuration, visualizations, etc.

Fireside chat

At the end of the meetup, Ramani Natarajan of Slalom and Yuan Tang of Uptake discussed:

• Why contributing to TensorFlow?
• Where do you see the opportunities for TensorFlow as a project?
• What will it take for large organizations to apply TensorFlow to real-world problems?

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Further reading

• The Diversity of TensorFlow: Wrappers, GPUs, Generative Adversarial Networks, etc.
• Under-the-Hood Mechanisms of Neural Networks with TensorFlow
• TensorFlow in Finance: Discussing Predictive Analytics and Budget Planning
• TensorFlow Cheat Sheet