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Related lectures (32)

Deep Learning: Convolutional Neural Networks and Training Techniques Log in to Mediaspace to watch this video

Discusses convolutional neural networks, their architecture, training techniques, and challenges like adversarial examples in deep learning.

Neural Networks: Learning Features & Linear Prediction Log in to Mediaspace to watch this video

Explores neural networks' ability to learn features and make linear predictions, emphasizing the importance of data quantity for effective performance.

Deep Learning: Multilayer Perceptron and Training Log in to Mediaspace to watch this video

Covers deep learning fundamentals, focusing on multilayer perceptrons and their training processes.

Deep Learning Fundamentals Log in to Mediaspace to watch this video

Introduces deep learning fundamentals, covering data representations, neural networks, and convolutional neural networks.

Deep Generative Models: Part 2 Log in to Mediaspace to watch this video

Explores deep generative models, including mixtures of multinomials, PCA, deep autoencoders, convolutional autoencoders, and GANs.

Neural Networks: Regression and Classification Log in to Mediaspace to watch this video

Explores neural networks for regression and classification tasks, covering training, regularization, and practical examples.

Neural Networks: Basics and Applications Log in to Mediaspace to watch this video

Explores neural networks basics, XOR problem, classification, and practical applications like weather data prediction.

Neural Networks for NLP Log in to Mediaspace to watch this video

Covers modern Neural Network approaches to NLP, focusing on word embeddings, Neural Networks for NLP tasks, and future Transfer Learning techniques.

Multi-layered Perceptron: History and Training Algorithm Log in to Mediaspace to watch this video

Explores the historical development and training of multi-layered perceptrons, emphasizing the backpropagation algorithm and feature design.

Neural Networks: Multilayer Perceptron Log in to Mediaspace to watch this video

Explores the history, models, training, convergence, and limitations of neural networks, including the backpropagation algorithm and universal approximation.

Deep Learning: Convolutional Networks Log in to Mediaspace to watch this video

Explores convolutional neural networks, backpropagation, and stochastic gradient descent in deep learning.

Deep Learning: Data Representations and Neural Networks Log in to Mediaspace to watch this video

Covers data representations, Bag of Words, histograms, data pre-processing, and neural networks.

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