CIFAR-10 Courses and Certifications

rupert ai

Image Classification with CIFAR 10 - Computer Vision Basics Ep. 1 Loading Data

Practical guide to image classification using CIFAR10 dataset. Learn to load data, create DataLoaders, transform images, and visualize the dataset in PyTorch for computer vision tasks.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

Arm Education

Introduction to AI

Explore the fundamentals of AI, from historical evolution to practical applications, covering machine learning concepts, neural networks, ethical considerations, and hands-on implementation with PyTorch.

• edX
• 12 weeks, 1-2 hours/week
• Self-Paced
• Free Online Course (Audit)

Packt

Advanced Generative Adversarial Networks (GANs)

Master AI-driven image synthesis with GANs. Learn architectures, implement models, and optimize performance using popular datasets. Apply knowledge to generate realistic images for practical applications.

• Coursera
• 12 hours 46 minutes
• Self-Paced
• 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
• Self-Paced
• Paid Course

Deep Learning Python Project: CNN based Image Classification

296 ratings at Udemy

Master Image Classification with CNN on CIFAR-10 dataset: A Deep Learning Project for Beginners using Python

• Udemy
• 1 hour 28 minutes
• Self-Paced
• Paid Course

Building a Vision Transformer Model from Scratch with PyTorch

Build a Vision Transformer from scratch with PyTorch, implementing patch embedding through Transformer Encoder, and train your model on CIFAR-10 for practical image classification experience.

• freeCodeCamp
• 2 hours 5 minutes
• Self-Paced
• Free Video

Outlier

Diffusion Models - PyTorch Implementation

1 rating

Learn to implement and train diffusion models in PyTorch, covering unconditional and conditional versions, classifier-free guidance, and exponential moving average. Gain hands-on experience with state-of-the-art generative AI techniques.

• YouTube
• 22 minutes
• Self-Paced
• 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
• Self-Paced
• Free Video

Alexander Amini;  MIT

Biologically Inspired Neural Networks

Explore biologically plausible learning algorithms for neural networks, inspired by brain function. Discover synaptic plasticity rules and their application in deep learning architectures.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

Code Sync

Comparing Elixir and Python for Simple Neural Networks

Compare Elixir's Nx library with Python's machine learning ecosystem for training neural networks. Explore development experiences and performance differences using MNIST and CIFAR-10 datasets.

• YouTube
• 38 minutes
• Self-Paced
• Free Video

Fields Institute

Premonitions of Public Data for Private ML

Explore how public data pre-training enhances private machine learning, examining its impact on accuracy, zero-shot learning, and the future of privacy-preserving AI techniques.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Google TechTalks

Differentially Private Diffusion Models Generate Useful Synthetic Images

Explore privacy-preserving synthetic image generation using diffusion models. Learn techniques for fine-tuning pre-trained models to achieve state-of-the-art results on CIFAR-10 and Camelyon17 datasets.

• YouTube
• 41 minutes
• Self-Paced
• Free Video

Data Science Conference

Google Colaboratory and Python: Deep Learning Basics for Computer Vision Tasks

Explore Google Colaboratory for deep learning in computer vision with Python, from creating interactive notebooks to building and training CNNs for image classification using the CIFAR-10 dataset.

• YouTube
• 1 hour 39 minutes
• Self-Paced
• Free Video

Yacine Mahdid

Continuous Thought Machine Deep Dive - Temporal Processing and Neural Synchronisation

Explore Continuous Thought Machines, a novel neural architecture with temporal processing through decoupled ticks, featuring hands-on demos and experiments across vision tasks.

• YouTube
• 1 hour 16 minutes
• Self-Paced
• Free Video

Data Science Conference

Google Colaboratory and Python: Deep Learning Basics for Computer Vision Tasks

Master Google Colab for image processing while learning Python fundamentals, CNN architecture, and hands-on model training using CIFAR-10 dataset for computer vision tasks.

• YouTube
• 1 hour 56 minutes
• Self-Paced
• Free Video