Batch Normalization Courses and Certifications

Yannic Kilcher

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

Explore how Batch Normalization accelerates deep network training by reducing internal covariate shift, enabling higher learning rates and improved model performance.

• YouTube
• 26 minutes
• On-Demand
• Free Online Course

DeepLearning.AI;  Stanford

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

63066 ratings at Coursera

Enhance deep learning skills: master hyperparameter tuning, regularization, optimization, and TensorFlow implementation for improved neural network performance and systematic results generation.

• Coursera
• 23 hours 35 minutes
• On-Demand
• Free Online Course (Audit)

Deep Learning: Convolutional Neural Networks in Python

5998 ratings at Udemy

Tensorflow 2 CNNs for Computer Vision, Natural Language Processing (NLP) +More! For Data Science & Machine Learning

• Udemy
• 13 hours 20 minutes
• On-Demand
• Paid Course

Intro to Deep Learning

2 reviews

Use TensorFlow and Keras to build and train neural networks for structured data.

• Kaggle
• 4 hours
• On-Demand
• Free Certificate

Deep Learning with PyTorch

12 ratings at DataCamp

Learn to create deep learning models with the PyTorch library.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

How Neural Networks Work

This video sequence tracks the lecture sequence in course 313 from the End to End Machine Learning School, How Neural Networks Work.

• YouTube
• 4 hours 30 minutes
• On-Demand
• Free Online Course

Convolution in Two Dimensions

Explore 2D convolution, softmax, and batch normalization. Build a CNN for MNIST digits using Cottonwood, covering model architecture, training, and evaluation techniques.

• YouTube
• 2 hours 30 minutes
• On-Demand
• Free Online Course

Great Learning

Batch Normalization

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.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Online Course

Yannic Kilcher

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

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.

• YouTube
• 34 minutes
• On-Demand
• Free Online Course

Yannic Kilcher

NVAE- A Deep Hierarchical Variational Autoencoder

Detailed explanation of NVAE, a deep hierarchical variational autoencoder for high-resolution image generation, covering architecture, training techniques, and state-of-the-art results.

• YouTube
• 34 minutes
• On-Demand
• Free Online Course

Andrej Karpathy

Building Makemore - Building a WaveNet

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.

• YouTube
• 56 minutes
• On-Demand
• Free Online Course

Andrej Karpathy

Building Makemore - Becoming a Backprop Ninja

Hands-on tutorial on manual backpropagation through a 2-layer MLP, enhancing understanding of gradient flow in neural networks for confident innovation and debugging.

• YouTube
• 1 hour 55 minutes
• On-Demand
• Free Online Course

Andrej Karpathy

Building Makemore - Activations & Gradients, BatchNorm

Explore MLP internals, activations, gradients, and BatchNorm. Learn to diagnose deep networks, understand training challenges, and implement modern techniques for improved performance.

• YouTube
• 1 hour 56 minutes
• On-Demand
• Free Online Course

DigitalSreeni

An Overview of Deep Learning and Neural Networks

Comprehensive introduction to deep learning concepts, covering neural networks, convolution, pooling, normalization, and more. Includes code examples for practical implementation.

• YouTube
• 34 minutes
• On-Demand
• Free Online Course

ICTP Mathematics

Eigenvalue Distribution for Non Linear Models of Random Matrices

Explore eigenvalue distribution in non-linear random matrix models, covering motivation, limits, batch normalization, and moment methods with speaker Sandrine PECHE.

• YouTube
• 43 minutes
• On-Demand
• Free Online Course