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Explore Meta AI's LLaMA language models with Yannic Kilcher in under an hour. Learn about training data, hyperparameters, architecture modifications, and more.
Learn to prune neural networks without data, understand the Lottery Ticket Hypothesis, and explore the SynFlow algorithm in less than an hour with Yannic Kilcher.
Explore visual transfer learning with Yannic Kilcher's concise guide, focusing on pre-training from high-quality samples on an image captioning task. Less than 1-hour workload.
Explore the Linformer model's efficient approach to Transformers' self-attention mechanism in this under 1-hour material by Yannic Kilcher.
Explore unsupervised neural machine translation for Python, C++, and Java code with Yannic Kilcher in under an hour. Learn about transcompiling problems, shared embeddings, and more.
Explore robust metrics for text generation with Yannic Kilcher in under an hour. Learn about BLEURT, a BERT-based evaluation metric, and its correlation with human judgments.
Explore Yannic Kilcher's efficient approach to Neural Architecture Search using a Synthetic Petri Dish model. Learn to predict model performance in less than an hour.
Explore object detection through CornerNet's unique approach of detecting objects as paired keypoints, with Yannic Kilcher. Less than 1 hour.
Explore the Synthesizer model and its impact on Transformers in this concise study by Yannic Kilcher. Learn about attention mechanisms, synthetic attention, and their applications in language modeling and translation.
Explore GPT-3's capabilities in NLP tasks with Yannic Kilcher's 1-2 hour material, covering language models, transformer models, fine-tuning, and experimental results.
Explore object detection in images using a single Transformer stacked on a CNN in this concise study by Yannic Kilcher. Learn about architecture, problem formulation, and results in under an hour.
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.
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