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 Video

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

63510 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
• Paid Course

deeplizard

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

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

Data Science Courses

Deep Learning: Dropout and Batch Normalization - Lecture 5

Delve into dropout and batch normalization techniques, understanding their mechanisms and effectiveness in deep learning, with insights on loss function smoothness and Lipschitzness.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Microcredential

Comprehensive Introduction to PyTorch

194 ratings at CodeSignal

Master PyTorch fundamentals through hands-on exercises, progressing from tensor basics to advanced neural networks and model optimization techniques using real-world datasets like wine classification.

• CodeSignal
• 11 hours
• On-Demand
• Free Certificate
• 4 courses

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 Video

PyTorch Techniques for Model Optimization

Master advanced PyTorch optimization techniques including regularization, dropout, batch normalization, and learning rate scheduling to enhance model performance and prevent overfitting.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Improving Neural Networks with PyTorch

Master advanced PyTorch techniques like dropout, early stopping, and batch normalization to transform weak neural networks into robust, high-performing models through hands-on implementation.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Advanced Neural Tuning

Master advanced neural network optimization through learning rate scheduling, optimizer comparison, and Xavier weight initialization techniques.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Time Series Forecasting with LSTMs

1 review

Master LSTM networks for time series forecasting with PyTorch, building optimized models that handle long-term dependencies and evaluating performance using RMSE, MAE, and MAPE metrics.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Deep Learning: Convolutional Neural Networks in Python

6531 ratings at Udemy

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

• Udemy
• 13 hours 54 minutes
• On-Demand
• Paid Course

Packt

Deep Learning: Convolutional Neural Networks with TensorFlow

Unlock the potential of deep learning by mastering Convolutional Neural Networks and Transfer Learning with hands-on TensorFlow and Keras experience for image and text classification.

• Coursera
• 5 hours 14 minutes
• On-Demand
• Paid Course

Intro to Deep Learning

4 reviews

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

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

CodeEmporium

Deep Learning 201 - Mathematical Foundations

Dive into neural networks' mathematical foundations covering activation functions, optimizers, CNNs, RNNs, LSTMs, GANs, and VAEs with practical explanations.

• YouTube
• 2 hours 19 minutes
• On-Demand
• Free Video