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Deep Learning Fundamentals

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Related lectures (43)

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: 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.

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

Explores data representations, histograms, neural networks, and deep learning concepts.

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

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

Neural Networks: Training and Optimization Log in to Mediaspace to watch this video

Explores the training and optimization of neural networks, addressing challenges like non-convex loss functions and local minima.

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 Recap: Activation Functions Log in to Mediaspace to watch this video

Covers the basics of neural networks, activation functions, training, image processing, CNNs, regularization, and dimensionality reduction methods.

Deep Neural Networks Log in to Mediaspace to watch this video

Covers the back-propagation algorithm for deep neural networks and the importance of locality in CNN.

Introduction to Data Science Log in to Mediaspace to watch this video

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Neural Networks: Training and Optimization Log in to Mediaspace to watch this video

Explores neural network training, optimization, and environmental considerations, with insights into PCA and K-means clustering.

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: Perceptron and Backpropagation Log in to Mediaspace to watch this video

Covers the basics of neural networks, including the perceptron model and backpropagation.

Image Processing II: Neural Networks and CNNs Log in to Mediaspace to watch this video

Explores the evolution of CNNs in image processing, covering classical and deep neural networks, training algorithms, backpropagation, non-linear steps, loss functions, and software frameworks.

Policy Gradient Methods in Reinforcement Learning Log in to Mediaspace to watch this video

Covers policy gradient methods in reinforcement learning, focusing on optimization techniques and practical applications like the cartpole problem.

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

Introduces fundamental machine learning concepts and algorithms for model training and evaluation.

Image Processing II: Bayesian Classification and Decision Making Log in to Mediaspace to watch this video

Explores Bayesian classification, decision making, and pattern recognition applications in image processing.

Principal Component Analysis: Eigenfaces Log in to Mediaspace to watch this video

Covers the application of Principal Component Analysis in facial recognition using a famous faces dataset.

Do ImageNet Classifiers Generalize?Log in to Mediaspace to watch this video

Examines the generalization of ImageNet classifiers, safety-critical applications, overfitting, and the reliability of machine learning models.

Coordinate Descent: Optimization Strategies Log in to Mediaspace to watch this video

Explores coordinate descent optimization strategies, emphasizing simplicity in optimization through one-coordinate updates and discussing the implications of different approaches.

Bias-Variance Trade-Off Log in to Mediaspace to watch this video

Explores underfitting, overfitting, and the bias-variance trade-off in machine learning models.

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