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In this meetup we wanted to talk about the basics of training neural networks and how they fit in within the deep learning landscape, as well as discuss exactly what deep learning is, where it came from, and why it works (and when it doesn't). We also wanted to give some hands-on examples of how these models can be used in Python through the Scikit-Learn and Tensorflow libraries.
Together, these Python-based technologies represent one of the most popular, state-of-the-art solutions for open source machine learning problems and are currently used in commercialized products by companies like Google (Tensorflow Creators), Twitter, eBay, Dropbox, Uber, and SAP.
• Artificial Neural Network (ANN) Introduction
• ANN training examples with Scikit-Learn
• Deep Learning Introduction
• Tensorflow Basics
• ANN training examples with Tensorflow
For anyone with a little patience, you might try installing Anaconda, Numpy, Pandas, Scikit-Learn, Tensorflow, and Jupyter yourself to be able to follow along (it's not as bad is it sounds since they almost all install through the same process), but generally speaking I think this will be more of a walk-through that includes how to set those up and why it's worth the effort.
Links to Python Notebooks for this talk:
For source code files, see our Python Notebook Repo