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Explore BERT model pruning and the Lottery Ticket Hypothesis with Yannic Kilcher. Learn how even "bad" subnetworks can be fine-tuned for good accuracy in under an hour.
Explore meta-learning with implicit gradients in under an hour with Yannic Kilcher. Understand the computational benefits of iMAML and its application in few-shot image recognition.
Learn to build a sentiment classifier using PyTorch and Huggingface's NLP library in a 1-2 hour tutorial by Yannic Kilcher.
Explore the world of self-supervised learning with Yannic Kilcher's under 1-hour material. Dive into intrinsic rewards, planning in latent space, and maximizing information gain.
Explore machine learning with Yannic Kilcher in less than an hour. Learn about DreamCoder, a system that solves problems by writing programs, and its potential in deep learning.
Explore DeepMind's Perceiver model with Yannic Kilcher in under an hour. Understand its architecture, built-in assumptions, and how it solves the quadratic bottleneck problem.
Explore the potential of pretrained transformers in machine learning across different modalities with Yannic Kilcher. Learn about fine-tuning, modality transfer, and network architecture in under an hour.
Explore the future of AI with Yannic Kilcher's deep dive into Self-Supervised Learning (SSL), discussing its potential to reduce label dependency and enhance knowledge transfer in under an hour.
Explore the inner workings of OpenAI's CLIP model with Yannic Kilcher in less than an hour. Understand how neurons respond to distinct concepts across multiple modalities.
Explore Geoff Hinton's GLOM model for AI visual scene understanding in this 1-2 hour material by Yannic Kilcher. Learn about object recognition, capsule networks, and GLOM architecture.
Explore DeBERTa, Microsoft's advanced BERT-style Self-Attention Transformer model, in this short, comprehensive study by Yannic Kilcher. Learn about disentangled attention, relative positional encodings, and more.
Explore the advancements in Model-Based Reinforcement Learning with this under 1-hour material by Yannic Kilcher. Learn about world models, latent states, and achieve state-of-the-art single-GPU performance in Atari.
Explore TransGAN, the first GAN with both generator and discriminator as transformers, in this less than 1-hour study by Yannic Kilcher. Learn about its architecture, tricks for training, and results.
Explore the benefits and drawbacks of Batch Normalization in deep learning with Yannic Kilcher. Learn about Normalizer-Free Networks and adaptive gradient clipping in under an hour.
Explore the Nyströmformer algorithm for approximating Self-Attention in Transformers with Yannic Kilcher. Learn about its linear memory and time requirements, and its application in Natural Language Processing.
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