Building Recurrent Neural Networks Using Python and TensorFlow
What this course is about:

This is a short course on how machine learning and neural networks can be applied to solving language-related problems like sentiment analysis and topic classification.

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.

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.

You will learn:
  1. What are Neural Networks And Why Does Everyone Suddenly Care About Them?
  2. Why is Natural Language Processing (NLP) Difficult?
  3. The Difference Between Supervised and Unsupervised Learning Algorithms
  4. The Representation of Words as Vectors
  5. Garbage In, Garbage Out: Always Preprocess Your Data!
  6. Building Recurrent Neural Networks Using Python and TensorFlow
  7. Putting it All Together : Topic Classification and Sentiment Analysis
Prerequisites & Preparation:
  1. Basic Python Programming Skills
  2. Laptop

Start Dates

Jan 23rd Evening


Course schedule:
Jan. 23, 2018, 6:30 p.m.
Jan. 30, 2018, 6:30 p.m.

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