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