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