This course is Mostly for People Who Like Programming, and In Particular People Who Like Programming in Python

Intro to Neural Networks for Natural Language Processing
What this course is about:

Intro to Neural Networks for Natural Language Processing. Today’s modern machine learning libraries have thoughtful, high-level APIs that allow *anyone* who is comfortable with code to dive in to construction of real-world Neural Networks(NNs) using Deep Learning. Combining Keras and TensorFlow together allows us to learn about how to use NNs and deep learning while abstracting away from a ton of details and keeping the big picture in mind. Total in-Class Hours: 7,5

Important Note: This is not a neural network or Deep Learning theory class. We absolutely will spend time talking about the theory of NNs because we want to pull back the veil a bit and we want to make sure you complete the course with a conceptual understanding of Neural Networks and Deep Learning. But the majority of our time will be spent writing and reading and debugging code written in the high-level parts of the APIs of Keras and TensorFlow. This will let us learn how to write basic Neural Net related programs.

Who this program is for:

This course is for people who 1) want to get a sense of what Deep Learning is all about and 2) who’d like to use the high-level libraries Keras and TensorFlow to write code that implement the basics of Deep Learning on their own laptops or in the cloud via Jupyter Notebooks.

What is Deep Learning?

What is the Difference Between a Convolutional Neural Network and a Recurrent Neural Network? Stand On The Shoulders of Giants: With Modern, High Level APIs, Big Data Is *Not* Always Needed For Deep Learning. Let’s Code An Image Recognition and Classification Problem in Keras Using A Convolutional Neural Networks. Let’s Code A Natural Language Processing Problem in Keras Using A Recurrent Neural Networks The Care and Feeding of Neural Networks: Hyperparameters, Optimization Functions, Activation Functions, Fully Connected Layers, and Other Things The Make Neural Networks Go. Using TensorBoard, TensorFlow’s Great Visualization Tool For Neural Networks

You will learn:
  1. What are Neural Networks And Why Does Everyone Suddenly Care About Them?
  2. What Sorts of Data Science Problems Can Neural Networks Solve?
  3. State of the Art 2017 versus State of the Art 2012: Exactly How Much Has the World Changed In The Last Five Years?
  4. Introduction to Keras and TensorFlow: Learn to Code Neural Networks Using Python
  5. Building Recurrent Neural Networks Using Python and TensorFlow
  6. The Representation of Words as Vectors
  7. Putting it All Together : Topic Classification and Sentiment Analysis
Prerequisites & Preparation:
  1. Python Programming 101
  2. Laptop
  3. Laptop

Start Dates

Nov 9th Evenings


Course schedule:
Nov. 9, 2017, 6:30 p.m.
Nov. 16, 2017, 6:30 p.m.


TensorFlow is a powerful open-source software library for machine learning developed by researchers at Google

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