Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Lecture

Deep Learning Building Blocks: Linear Layers

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (51)

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.

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.

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.

Deep Learning: Data, Models, and Challenges Log in to Mediaspace to watch this video

Provides an overview of deep learning concepts, focusing on data, model architecture, and challenges in handling large datasets.

Deep Learning Log in to Mediaspace to watch this video

Covers the fundamentals of deep learning, including data representations, bag of words, data pre-processing, artificial neural networks, and convolutional neural networks.

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

Explores the logic of neuronal function, the Perceptron model, deep learning applications, and levels of abstraction in neural models.

Document Analysis: Topic Modeling Log in to Mediaspace to watch this video

Explores document analysis, topic modeling, and generative models for data generation in machine learning.

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.

Reinforcement Learning Concepts Log in to Mediaspace to watch this video

Covers key concepts in reinforcement learning, neural networks, clustering, and unsupervised learning, emphasizing their applications and challenges.

Foundations of Deep Learning: Transformer Architecture Overview Log in to Mediaspace to watch this video

Covers the foundational concepts of deep learning and the Transformer architecture, focusing on neural networks, attention mechanisms, and their applications in sequence modeling tasks.

Efficient Machine Learning via Data Summarization Log in to Mediaspace to watch this video

Explores efficient machine learning through data summarization, covering challenges, methods, and impactful applications in various domains.

Neuroscience and Machine Learning: Understanding Visual Intelligence Log in to Mediaspace to watch this video

Explores the relationship between neuroscience and machine learning in visual intelligence.

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 Architectures for Embodied AI and Cognition Log in to Mediaspace to watch this video

Explores neural architectures for embodied AI, cognitive systems, and the integration of computing and robotics.

Deep Learning: Dimensionality and Data Representation Log in to Mediaspace to watch this video

Delves into deep learning's dimensionality, data representation, and performance in classifying large-dimensional data, exploring the curse of dimensionality and the neural tangent kernel.

Data Representations and Processing in Machine Learning Log in to Mediaspace to watch this video

Covers data representations and processing techniques essential for effective machine learning algorithms.

Monotonicity Criteria in Differentiable Functions Log in to Mediaspace to watch this video

Explores monotonicity criteria, L'Hopital's rule, and Lipschitz continuity in differentiable functions and deep neural networks.

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.

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.

Page 2 of 3