Machine Learning and Deep Learning for Computer Vision
Teachers: Andrè Panisson, Alan Perotti — ISI Foundation
This in-depth part of the course allows to build an appealing and diversified Machine Learning portfolio. It starts with a Machine Learning introduction and application with Scikit-learn, and continues with Neural Networks and backpropagation lectures where you’ll start exploring Computer Vision techniques on a dataset of images.
Deep Learning methods. You’ll be challenged to use TensorFlow and Keras on a image classification real cases. The workshop ends with lessons in Transfer Learning and one last project building your data set by scraping Google images and practicing everything you learned.
Prerequisites: Python, Pandas, Statistics, exposure to Machine Learning is welcome.
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