Explores active learning strategies for selecting the most valuable data to label when working with a limited labeling budget in machine learning.
Practical strategies for staying current in the fast-moving field of machine learning, including project experimentation and community engagement.
A tutorial on fine-tuning a Vision Transformer (ViT) model for satellite image classification using Hugging Face Transformers and Keras.
A comprehensive list of 90 machine learning lecture videos covering topics from Python basics to advanced ML concepts like decision trees and Bayesian methods.
A comprehensive collection of 90 machine learning lecture videos covering Python, scikit-learn, algorithms, and model evaluation techniques.
A summary of key papers and talks from the RecSys 2021 conference, focusing on collaborative filtering, model comparisons, and deployment strategies.
A forecast of speech recognition technology's evolution from 2010 to 2030, analyzing past progress and predicting future trends.
An in-depth technical explanation of diffusion models, a class of generative AI models that create data by reversing a noise-adding process.
A comprehensive deep learning course covering fundamentals, neural networks, computer vision, and generative models using PyTorch.
A comprehensive deep learning course overview with PyTorch tutorials, covering fundamentals, neural networks, and advanced topics like CNNs and GANs.
Explains contrastive representation learning, its objectives like contrastive and triplet loss, and its use in supervised and unsupervised machine learning.
Explores how Stochastic Gradient Descent (SGD) inherently prefers certain minima, leading to better generalization in deep learning, beyond classical theory.
A technical exploration of the β-VAE objective from an information maximization perspective, discussing its role in learning disentangled representations.
A curated list of public dataset repositories for machine learning and deep learning projects, including computer vision and NLP datasets.
A curated list of public dataset repositories for machine learning and deep learning projects, including sources for computer vision, NLP, and more.
A review of the book 'Deep Learning with PyTorch', covering its structure, content, and suitability for students and beginners in deep learning.
A detailed review of the book 'Deep Learning with PyTorch,' covering its structure, content, and suitability for students and practitioners.
An analysis of GPT-3's capabilities, potential for misuse in generating fake news and spam, and its exclusive licensing by Microsoft.
Explores whether deep learning creates a new kind of program, using the philosophy of operationalism to compare it with traditional programming.
Key takeaways from RecSys 2020 conference, focusing on ethics, bias, sequence models, and notable papers in recommender systems.
