Non Llm Neural Networks Ml Foundations
138 resources · page 3 of 5
AssemblyAI engineering blog
by AssemblyAI
AssemblyAI blog with guides, model launches and voice-agent builds for speech AI.
Easy-RL / 蘑菇书
by Datawhale
Datawhale Easy-RL GitHub repo: Chinese reinforcement-learning tutorial (Mushroom Book) with code.
Full Stack Deep Learning
Full Stack Deep Learning site with course materials and LLM Bootcamp lectures on building AI-powered products.
Karpathy: Unreasonable Effectiveness of RNNs
by Andrej
Andrej Karpathy's 2015 essay The Unreasonable Effectiveness of Recurrent Neural Networks, with char-RNN examples.
LightGBM documentation
LightGBM documentation: gradient boosting framework with tree-based learning, tuning guides and distributed training.
Recurrent Neural Networks and LSTM (Jürgen Schmidhuber)
Jürgen Schmidhuber's IDSIA page on recurrent neural networks and LSTM, with history and references.
NYU Deep Learning (LeCun/Canziani)
NYU Deep Learning course (Spring 2021) by Yann LeCun and Alfredo Canziani, with lectures, labs and notebooks.
OECD AI Recommendation (OECD-LEGAL-0449)
by OECD
OECD Recommendation of the Council on Artificial Intelligence, the source of the OECD AI Principles and AI system definition.
PDE-Transformer
by TUM Physics-based Simulation
PDE-Transformer project page: transformer architecture for learning partial differential equations from data.
Physics-based Deep Learning (TUM)
by Nils Thuerey et al. (TU Munich)
Physics-based Deep Learning book from TUM: hands-on guide to combining physical simulation with deep learning.
PointNet
by Charles R. Qi et al. (Stanford University)
PointNet project page: deep network architecture that consumes raw point clouds for 3D classification and segmentation.
Roboflow documentation
by Roboflow
Roboflow documentation for building computer-vision datasets, training models and deploying them.
sktime
by sktime
sktime: open-source Python framework for time-series forecasting, classification and anomaly detection.
Soniox Docs: Models
by Soniox
Soniox models page listing speech-to-text model versions, changelog and deprecations.
Speechmatics technical articles
by Speechmatics
Speechmatics articles on speech recognition technology, product news and AI research.
UvA Deep Learning tutorials
by Phillip Lippe (University of Amsterdam)
University of Amsterdam deep learning tutorial notebooks in PyTorch and JAX/Flax, covering core architectures.
XGBoost documentation
XGBoost documentation: distributed gradient boosting library with training, GPU support and parameter guides.
YSDA Practical Deep Learning
by Yandex School of Data Analysis
YSDA Practical_DL GitHub repo: deep learning course materials from Yandex School of Data Analysis, HSE and Skoltech.
YSDA Practical RL
by Yandex School of Data Analysis
YSDA Practical_RL GitHub repo: open reinforcement-learning course with notebooks and assignments from HSE and YSDA.
Zoom Scribe API documentation
by Zoom
Zoom Scribe API documentation: transcription service for many media formats, with modes and authentication details.
Agent57
by Adrià Puigdomènech Badia et al. (Google)
arXiv paper (2020) introducing Agent57, the first agent to exceed the human baseline on all 57 Atari games.
ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)
by Alex Krizhevsky, Ilya Sutskever and Geoffrey E. Hinton (University of Toronto)
NeurIPS paper (PDF, 2012) AlexNet: ImageNet classification with deep convolutional neural networks.
Faster sorting algorithms discovered using deep reinforcement learning (AlphaDev)
by Daniel J. Mankowitz et al. (Google DeepMind)
Nature paper (2023) on AlphaDev discovering faster sorting algorithms with deep RL.
Mastering the game of Go with deep neural networks and tree search (AlphaGo)
by David Silver et al. (DeepMind)
Nature paper (2016) on AlphaGo, mastering Go with deep neural networks and tree search.
Grandmaster level in StarCraft II using multi-agent reinforcement learning (AlphaStar)
by Oriol Vinyals et al. (DeepMind)
Nature paper (2019) on AlphaStar reaching grandmaster level in StarCraft II with multi-agent RL.
Discovering faster matrix multiplication algorithms with reinforcement learning (AlphaTensor)
by Alhussein Fawzi et al. (Google DeepMind)
Nature paper (2022) on AlphaTensor discovering faster matrix multiplication algorithms with RL.
AlphaZero
by David Silver et al. (DeepMind)
arXiv paper (2017) introducing AlphaZero, mastering chess and shogi through self-play reinforcement learning.
Chronos: Learning the Language of Time Series
by Abdul Fatir Ansari et al. (Amazon)
arXiv paper (2024) introducing Chronos, pretrained time-series forecasting models using language-model tokenization.
CLIP
by Alec Radford et al. (OpenAI)
arXiv paper (2021) introducing CLIP, contrastive language-image pretraining for transferable visual models.
DenseNet
by Gao Huang et al. (Cornell University)
arXiv paper (2016) "Densely Connected Convolutional Networks", introducing DenseNet, where each layer receives feature maps from all earlier layers.
DETR
by Nicolas Carion et al. (Meta)
arXiv HTML version of the DETR paper (2020) on end-to-end object detection with transformers.
DINOv2: Learning Robust Visual Features without Supervision
by Maxime Oquab et al. (Meta AI)
arXiv HTML version of the DINOv2 paper (2023) on self-supervised visual features.