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Related lectures (30)

Feed-forward Networks Log in to Mediaspace to watch this video

Introduces feed-forward networks, covering neural network structure, training, activation functions, and optimization, with applications in forecasting and finance.

Deep Learning for NLP Log in to Mediaspace to watch this video

Explores deep learning for NLP, covering word embeddings, context representations, learning techniques, and challenges like vanishing gradients and ethical considerations.

Deep Neural Networks and Splines Log in to Mediaspace to watch this video

Covers the fundamentals of deep neural networks and splines, exploring their properties, implications, and applications in modern machine learning.

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.

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.

Machine Translation: Attention Mechanism Log in to Mediaspace to watch this video

Explores the attention mechanism in machine translation, addressing the bottleneck problem and improving NMT performance significantly.

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.

Neuroprosthetics: Brain Repair After Stroke Log in to Mediaspace to watch this video

Explores brain repair after stroke, covering changes post-stroke, therapies like vagus nerve stimulation, and growth factors.

Optimization in Machine Learning Log in to Mediaspace to watch this video

Explores optimization techniques, word embeddings, and recommendation systems in machine learning.

Linear Models: Part 2 Log in to Mediaspace to watch this video

Covers linear models, binary and multi-class classification, and logistic regression with practical examples.

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