ImageNet Courses and Certifications

Paul G. Allen School

Do ImageNet Classifiers Generalize to ImageNet? - Analyzing ML Progress and Challenges

Analyzing ImageNet classifiers' generalization, exploring overfitting and distribution shift in ML benchmarks, and addressing robustness issues like adversarial examples to improve machine learning reliability.

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

James Briggs

AlexNet and ImageNet Explained

Explore the revolutionary AlexNet CNN and ImageNet dataset, their impact on deep learning, and practical implementation using PyTorch for image classification tasks.

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

MITCBMM

Vision Beyond ImageNet - Understanding the Brain Mechanisms Underlying Visual Recognition

Discover how the brain processes visual information beyond traditional computer vision datasets, exploring neural mechanisms that enable human visual recognition capabilities.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video

Coursera

Preparing Images for AI Models

Discover essential techniques for sourcing, preprocessing, and augmenting image datasets to train robust diffusion models with production-ready workflows.

• Coursera
• 7 hours 59 minutes
• On-Demand
• Paid Course

Yannic Kilcher

Self-Training With Noisy Student Improves ImageNet Classification - Paper Explained

Explore a novel semi-supervised learning approach for image classification using unlabeled data, improving model performance and robustness through iterative self-training and noise injection techniques.

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

Yannic Kilcher

Do ImageNet Classifiers Generalize to ImageNet? - Paper Explained

Exploring ImageNet classifiers' generalization capabilities through new test datasets, revealing surprising accuracy drops and insights into model performance on slightly "harder" images.

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

Yannic Kilcher

ImageNet Classification with Deep Convolutional Neural Networks - Paper Explained

Detailed explanation of AlexNet, the groundbreaking deep convolutional neural network that revolutionized computer vision and kickstarted the deep learning era in image classification.

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

Simons Institute

A Data-Centric View on Reliable Generalization - From ImageNet to LAION-5B

Exploring CLIP model's robustness, fine-tuning methods, and the impact of pre-training datasets on reliable generalization in image-text learning, with insights from LAION-5B and DataComp experiments.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Computer Vision for Data Scientists

102 ratings at LinkedIn Learning

Get a comprehensive introduction to computer vision and learn how to train models and neural networks for image classification.

• LinkedIn Learning
• 4 hours 2 minutes
• On-Demand
• Free Trial Available

James Briggs

Computer Vision and Search Course

Discover computer vision techniques for search applications, from color histograms to CLIP models, with hands-on PyTorch implementations and zero-shot classification methods.

• YouTube
• 4 hours 34 minutes
• On-Demand
• Free Video

The Full Stack

Introduction to Deep Learning - Full Stack Deep Learning - March 2019

1 review

Comprehensive introduction to AI and deep learning, covering key concepts, applications, and historical context. Explores data processing, computational requirements, and course structure.

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

Python Simplified

Inference with Torch-TensorRT Deep Learning Prediction for Beginners - CPU vs CUDA vs TensorRT

Accelerate deep learning inference using Torch-TensorRT. Compare CPU, CUDA, and TensorRT performance with ResNet50 for image classification. Hands-on tutorial covers setup, implementation, and benchmarking.

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

Finnish Center for Artificial Intelligence FCAI

Elucidating the Design Space of Diffusion-Based Generative Models

Explore advancements in diffusion-based generative models, including improved sampling, training, and score network preconditioning. Learn about state-of-the-art results and modular design changes for enhanced efficiency and quality.

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

1littlecoder

Zero-Shot Image Classification with OpenAI's CLIP Model

Explore OpenAI's CLIP model for zero-shot image classification, demonstrating its ability to predict relevant text for images using natural language instructions without task-specific training.

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

Paul G. Allen School

Fast and Accurate Deep Neural Networks Training

Exploring LARS and LAMB optimizers for scaling deep learning on supercomputers, enabling faster training and higher accuracy in AI applications across various industries.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video