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AI / Machine Learning

Neural Networks

A hands-on neural networks course built around TensorFlow and Keras: tensor fundamentals and automatic differentiation, linear regression via gradient descent, the perceptron and logic gates, the XOR problem and why depth matters, building a multi-layer network from scratch, the Keras Sequential and Functional APIs, convolutional neural networks for images, transfer learning, and recurrent networks (LSTM) for text classification.

10 lessons
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Neural Networks

Lessons

  1. 1Lab 1: Introduction to Python for Data Science45 min read
  2. 2Introduction to TensorFlow 2.x10 min read
  3. 3ML Review and Gradient Descent Example12 min read
  4. 4Setup8 min read
  5. 5Building Neural Networks with TensorFlow 2.x Core API7 min read
  6. 6Keras Sequential model14 min read
  7. 7Neural Networks Assignment – Fashion MNIST with Keras2 min read
  8. 8Building a CNN to classify images in the CIFAR-10 Dataset11 min read
  9. 9Lesson 089 min read
  10. 10LSTM on 20 Newsgroups Dataset using Keras8 min read