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for YouTube Deep Learning CoursesMIT Introduction to Deep Learning 6S191
MIT's Introduction to Deep Learning 6.S191 is a comprehensive course for those interested in learning the foundations of deep learning. Led by Alexander Amini, the course covers topics such as the perceptron, neural networks, loss functions, training and gradient descent, backpropagation, setting the learning rate, batched gradient descent, and regularization. With slides and lab materials available at http://introtodeeplearning.com/, this course is perfect for those looking to gain a better understanding of deep learning. Subscribe to stay up to date with new lectures or follow @MITDeepLearning on Twitter and Instagram to stay connected! View all
Theory of Neural Networks - Deep Learning Without Frameworks
Get a comprehensive overview of Theory of Neural Networks - Deep Learning Without Frameworks View all
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Applied Deep Learning with PyTorch - Full Course
This comprehensive course provides an in-depth exploration of deep learning concepts and their application to a real-world project using PyTorch and Python. Learners will gain an understanding of the key principles behind deep learning and how to apply them to their own projects. View all
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