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#Batch Normalization

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Broad Institute

Meaningful Signals Within Deep Learning Models for Biology - Primer and Meeting

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Explore deep learning models in biology, from curating meaningful pre-training data to disentangling experimental noise, enhancing performance in biomedical imaging and high-throughput microscopy experiments.
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3 Lesons
1 hour 31 minutes
On-Demand
Free-Video
Great Learning

Batch Normalization

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Explore batch normalization in deep learning: its implementation, benefits, and impact on network performance. Learn when and how to use it effectively for improved model training.
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10 Lesons
1 hour 13 minutes
On-Demand
Free-Video

Convolution in Two Dimensions

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Explore 2D convolution, softmax, and batch normalization. Build a CNN for MNIST digits using Cottonwood, covering model architecture, training, and evaluation techniques.
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20 Lesons
2 hours 30 minutes
On-Demand
Free-Video

How Neural Networks Work

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This video sequence tracks the lecture sequence in course 313 from the End to End Machine Learning School, How Neural Networks Work.
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9 Lesons
4 hours 30 minutes
On-Demand
Free-Video
DigitalSreeni

An Overview of Deep Learning and Neural Networks

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Comprehensive introduction to deep learning concepts, covering neural networks, convolution, pooling, normalization, and more. Includes code examples for practical implementation.
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11 Lesons
34 minutes
On-Demand
Free-Video
ICTP Mathematics

Eigenvalue Distribution for Non Linear Models of Random Matrices

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Explore eigenvalue distribution in non-linear random matrix models, covering motivation, limits, batch normalization, and moment methods with speaker Sandrine PECHE.
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13 Lesons
43 minutes
On-Demand
Free-Video
Data Science Courses

Deep Learning: Dropout and Batch Normalization - Lecture 5

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Delve into dropout and batch normalization techniques, understanding their mechanisms and effectiveness in deep learning, with insights on loss function smoothness and Lipschitzness.
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1 Lesons
1 hour 7 minutes
On-Demand
Free-Video
Andrej Karpathy

Building Makemore - Building a WaveNet

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Dive deep into building a WaveNet-like convolutional neural network, exploring torch.nn, and understanding the typical deep learning development process through hands-on implementation.
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18 Lesons
56 minutes
On-Demand
Free-Video
Andrej Karpathy

Building Makemore - Becoming a Backprop Ninja

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Hands-on tutorial on manual backpropagation through a 2-layer MLP, enhancing understanding of gradient flow in neural networks for confident innovation and debugging.
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8 Lesons
1 hour 55 minutes
On-Demand
Free-Video
Andrej Karpathy

Building Makemore - Activations & Gradients, BatchNorm

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Explore MLP internals, activations, gradients, and BatchNorm. Learn to diagnose deep networks, understand training challenges, and implement modern techniques for improved performance.
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17 Lesons
1 hour 56 minutes
On-Demand
Free-Video
Yannic Kilcher

NFNets - High-Performance Large-Scale Image Recognition Without Normalization

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Explore Normalizer-Free Networks, a novel approach to image recognition that achieves state-of-the-art accuracy without batch normalization, offering faster training and improved transfer learning performance.
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12 Lesons
34 minutes
On-Demand
Free-Video
Yannic Kilcher

NVAE- A Deep Hierarchical Variational Autoencoder

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Detailed explanation of NVAE, a deep hierarchical variational autoencoder for high-resolution image generation, covering architecture, training techniques, and state-of-the-art results.
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10 Lesons
34 minutes
On-Demand
Free-Video
deeplizard

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

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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.
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8 Lesons
20 minutes
On-Demand
Free-Video
Yannic Kilcher

Group Normalization - Paper Explained

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Explore Group Normalization as an alternative to Batch Normalization, addressing batch size limitations and improving performance in various deep learning tasks.
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1 Lesons
29 minutes
On-Demand
Free-Video
Yannic Kilcher

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

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Explore how Batch Normalization accelerates deep network training by reducing internal covariate shift, enabling higher learning rates and improved model performance.
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5 Lesons
26 minutes
On-Demand
Free-Video
Manolis Kellis

Training Neural Networks and Deep Learning Optimization Methods - Lecture 16

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Master neural network training fundamentals, from momentum methods and regularization to batch normalization, with practical applications in BBB transmission prediction and model optimization.
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9 Lesons
1 hour 17 minutes
On-Demand
Free-Video