Deep Learning

Deep Learning is a subset of Machine Learning focusing on Neural Networks as an approach to ML-related problems. Like all ML, you can think of Deep Learning as function approximation. In recent years, it has exploded in popularity and can solve many tasks effectively!

For example, deep learning is used in:

  • Facial recognition

  • Translation (like Google Translate)

  • Medical diagnosis

The difference between deep learning and other ML techniques is that instead of relying solely on handcrafted features designed by the programmer, deep learning can learn important features in the data automatically through training, which improves its performance.

Deep learning tools are notoriously hard to use, so it's probably best not to use them in your term project. BUT, some common modules for deep learning are:

  • PyTorch

  • Keras

  • Tensorflow

PyTorch is probably the most usable, but by no means is it easy. Beware if you attempt to use it! The learning curve is very high.

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