Skip to main content
Graph
Search
fr
|
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Regularization by Early Stopping
Graph Chatbot
Related lectures (32)
Previous
Page 1 of 4
Next
Neural Networks: Training and Activation
Explores neural networks, activation functions, backpropagation, and PyTorch implementation.
Overfitting: Symptoms and Characteristics
Explores overfitting in polynomial regression, emphasizing the importance of generalization in machine learning and statistics.
Neural Networks: Regression and Classification
Explores neural networks for regression and classification tasks, covering training, regularization, and practical examples.
Neural Networks: Basics and Applications
Explores neural networks basics, XOR problem, classification, and practical applications like weather data prediction.
Deep Learning: Convolutional Neural Networks and Training Techniques
Discusses convolutional neural networks, their architecture, training techniques, and challenges like adversarial examples in deep learning.
Deep Neural Networks: Training and Optimization
Explores deep neural network training, optimization, preventing overfitting, and different network architectures.
Deep Learning: Data Representations and Neural Networks
Covers data representations, Bag of Words, histograms, data pre-processing, and neural networks.
Regularization Methods: Training and Validation Base
Explores regularization methods in neural networks, emphasizing the importance of training and validation bases to prevent overfitting.
Neural Networks: Regularization & Optimization
Explores neural network regularization, optimization, and practical implementation tips.
Statistical Learning: Fundamentals
Introduces the fundamentals of statistical learning, covering supervised learning, decision theory, risk minimization, and overfitting.