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Learn Backpropagation online: university courses, full YouTube courses, and courses with free certificates, from the IITs, MIT, Harvard, Google, Microsoft and more.
00:00:00 - Introduction 00:00:15 - Neural Networks 00:05:41 - Activation Functions 00:07:47 - Neural Network Structure 00:16:02 - Gradient Descent 00:30:00 - Multilayer Neural Networks 00:32:58 - Backpropagation 00:36:27 - Overfitting 00:38:52 - TensorFlow 00:53:01 - Computer Vision 00:58:09 - Imag…
University of Colorado Boulder
Introduction to Deep Learning provides a rigorous, concept-driven introduction to the models that power modern AI systems—from image recognition to large language models. You’ll build neural networks from first principles, understanding how forward passes, loss functions, and backpropagation enable…
Learn the basics of neural networks and backpropagation, one of the most important algorithms for the modern world.
Alison
Have you been wondering what a machine learning system can do? Chatbots, predictive text, apps for language translation, Netflix's recommendations, and social media feeds are all machine learning products. The course will illustrate the components of artificial neural networks with the steps for pe…
Northeastern University
This is Part 1 of a two-part graduate sequence in deep learning. It establishes the foundations of modern deep learning and the core neural architectures behind today's AI systems. You will build from how neural networks learn—through forward propagation and backpropagation—to convolutional network…
This live stream is a continuation of neural network series. I attempt to discuss backpropagation, but it mostly goes haywire. Timestamps: 30:20 - Reading Random Numbers 36:22 - Backpropagation Part 1 1:06:56 - Backpropagation Part 2 1:40:25 - Learning with Gradient Descent 🚂 Website: http://thecod…
In this live stream, I make another attempt to discuss backpropagation with gradient descent. I also solve XOR with the new toy neural network library. 23:57 - Gradient Descent video 1:46:27 - 2nd Gradient Descent video 2:14:50 - XOR Coding Challenge Schedule and topics: https://github.com/CodingTr…
Edureka
This course guides you through the foundational principles behind neural networks and computer vision systems, focusing on how forward propagation, backpropagation, optimization, and convolutional architectures enable modern AI applications. Through hands-on demonstrations and practical exercises,…
CodeSignal
Build Neural Networks from scratch with C++. Master every detail, from neurons to backpropagation, and apply your own library to real-world ML challenges.
CodeSignal
Build neural networks from scratch with Python and NumPy, from dense layers and activation functions to backpropagation and optimization. Package your components into a reusable library and apply it to a regression problem.
Udacity
Learn the fundamentals of neural networks with Python and TensorFlow, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images.
CodeSignal
Build a neural network library from scratch in R and understand how each component works. Master every detail, from neurons to backpropagation, and apply your own library to real-world ML challenges.
CodeSignal
Build a neural network library from scratch in JavaScript and understand how each component works. Master every detail, from neurons to backpropagation, and apply your own library to real-world ML challenges.
Packt
Unlock the core concepts of backpropagation, gradients, and gradient descent, and learn to implement them in Python. Master the theory behind neural networks and gain hands-on coding experience by building your own model. In this course, you will embark on a comprehensive learning journey, starting…
Udacity
Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images.
Udacity
This course covers foundational deep learning theory and practice. We begin with how to think about deep learning and when it is the right tool to use. The course covers the fundamental algorithms of deep learning, deep learning architecture and goals, and interweaves the theory with implementation…
Udacity
Develop a strong foundation in Python programming for AI, utilizing tools like NumPy, pandas, and Matplotlib for data analysis and visualization. Learn how to use, build, and train machine learning models with popular Python libraries. Implement neural networks using PyTorch. Gain practical experie…
