deeplizard Courses

Batch Normalization in PyTorch - Adding Normalization to Convolutional Neural Network Layers

Learn to implement batch normalization in convolutional neural networks using PyTorch. Explore the benefits, create and compare networks, and optimize performance through hands-on coding and practical examples.

• YouTube
• 20 minutes
• On-Demand
• Free Video

PyTorch Sequential Models - Neural Networks Made Easy

Learn to build neural networks using PyTorch's Sequential class. Explore multiple ways to construct models, set random seeds for reproducibility, and understand the benefits of this approach for creating efficient deep learning architectures.

• YouTube
• 27 minutes
• On-Demand
• Free Video

PyTorch DataLoader Source Code Debugging - Batch Building and Normalization

Debugging session exploring PyTorch DataLoader's inner workings, focusing on data normalization, batch building, and parameter impacts. Insights into efficient data handling for deep learning projects.

• YouTube
• 22 minutes
• On-Demand
• Free Video

PyTorch Dataset Normalization Using torchvision.transforms.Normalize()

Learn to normalize datasets in PyTorch using torchvision.transforms.Normalize(). Explore feature scaling, standardization, and color channel normalization. Understand the impact on neural network training.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Terence McKenna on Art, Psychedelics, Culture, Creativity, and Consciousness

Philosopher McKenna explores the interplay of art, psychedelics, culture, and consciousness, examining the artist's role in society and psychedelics' impact on creativity and perception.

• YouTube
• 51 minutes
• On-Demand
• Free Video

AI Art Course Install and Setup - Automatic1111 and Stable Diffusion

Learn to set up Automatic1111 UI and Stable Diffusion for AI art creation. Hands-on approach with project-based learning to explore image generation using artificial intelligence.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Deep Q-Network Image Processing and Environment Management - Reinforcement Learning Code Project

Learn to manage environments and process images for deep Q-networks in reinforcement learning, focusing on the cart and pole problem implementation.

• YouTube
• 22 minutes
• On-Demand
• Free Video

CNN Confusion Matrix with PyTorch - Neural Network Programming

Learn to build, plot, and interpret a confusion matrix using PyTorch for neural network evaluation, including techniques for disabling gradient tracking and analyzing model performance across different classes.

• YouTube
• 24 minutes
• On-Demand
• Free Video

CNN Training Loop Explained - Neural Network Code Project

Learn to build a convolutional neural network training loop using Python and PyTorch. Gain practical skills in implementing deep learning algorithms for image processing tasks.

• YouTube
• 22 minutes
• On-Demand
• Free Video

CNN Weights - Learnable Parameters in PyTorch Neural Networks

Explore PyTorch's inner workings, including OOP concepts, convolutional and linear layer weight tensors, and matrix multiplication for deep learning in neural networks.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Build PyTorch CNN - Object-Oriented Neural Networks

Learn to build a convolutional neural network using PyTorch for computer vision and AI applications. Gain hands-on experience in implementing object-oriented neural network architectures.

• YouTube
• 23 minutes
• On-Demand
• Free Video