Five courses on neural networks: training and tuning, structuring projects, convolutional networks, sequence models and transformers.
A step up from the Machine Learning Specialization, also led by Andrew Ng. It covers how deep networks are built and trained, how to diagnose and improve them, and the architectures behind computer vision and language — convolutional networks, recurrent networks and transformers.
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Build, compare and evaluate a real classifier end to end, predicting penguin species from their measurements.
How neural networks turn inputs into predictions, how they learn with gradient descent, and how to train one in PyTorch.
Google's free, fast-paced introduction to machine learning, with videos, visualisations and exercises.