--- id: "/non-llm-neural-networks-ml-foundations/page/3/" title: "Non-LLM neural networks & ML foundations · page 3" url: "https://skillissue.dev/non-llm-neural-networks-ml-foundations/page/3/" --- # Non-LLM neural networks & ML foundations Non-LLM neural networks & ML foundations - [classical ML & statistics](/non-llm-neural-networks-ml-foundations/classical-ml-statistics/index.md) (8) - [generative theory](/non-llm-neural-networks-ml-foundations/generative-theory/index.md) (1) - [graph NNs](/non-llm-neural-networks-ml-foundations/graph-nns/index.md) (8) - [recommenders](/non-llm-neural-networks-ml-foundations/recommenders/index.md) (10) - [reinforcement learning](/non-llm-neural-networks-ml-foundations/reinforcement-learning/index.md) (41) - [sequence models](/non-llm-neural-networks-ml-foundations/sequence-models/index.md) (16) - [time series & tabular](/non-llm-neural-networks-ml-foundations/time-series-tabular/index.md) (10) - [vision](/non-llm-neural-networks-ml-foundations/vision/index.md) (44) [Beginner](/non-llm-neural-networks-ml-foundations/beginner/index.md) [Intermediate](/non-llm-neural-networks-ml-foundations/intermediate/index.md) [Advanced](/non-llm-neural-networks-ml-foundations/advanced/index.md) [Expert](/non-llm-neural-networks-ml-foundations/expert/index.md) 138 resources · page 3 of 5 - ### [AssemblyAI engineering blog](/foundations/llm-fundamentals/assemblyai-engineering-blog/index.md) by [AssemblyAI](https://assemblyai.com/) AssemblyAI blog with guides, model launches and voice-agent builds for speech AI. Intermediate learning_resource guide US en - ### [Easy-RL / 蘑菇书](/foundations/llm-fundamentals/easy-rl/index.md) by [Datawhale](https://datawhale.cn) Datawhale Easy-RL GitHub repo: Chinese reinforcement-learning tutorial (Mushroom Book) with code. Intermediate learning_resource course China zh - ### [Full Stack Deep Learning](/foundations/llm-fundamentals/full-stack-deep-learning/index.md) by [Full Stack Deep Learning](https://fullstackdeeplearning.com/) Full Stack Deep Learning site with course materials and LLM Bootcamp lectures on building AI-powered products. Intermediate learning_resource course US en - ### [Karpathy: Unreasonable Effectiveness of RNNs](/foundations/llm-fundamentals/karpathy-unreasonable-effectiveness-of-rnns/index.md) by [Andrej](https://x.com/karpathy) Andrej Karpathy's 2015 essay The Unreasonable Effectiveness of Recurrent Neural Networks, with char-RNN examples. Intermediate learning_resource guide West en - ### [LightGBM documentation](/foundations/llm-fundamentals/lightgbm-documentation/index.md) by [Microsoft (LightGBM)](https://github.com/microsoft/LightGBM) LightGBM documentation: gradient boosting framework with tree-based learning, tuning guides and distributed training. Intermediate learning_resource docs International en - ### [Recurrent Neural Networks and LSTM (Jürgen Schmidhuber)](/foundations/llm-fundamentals/lstm/index.md) by [Jürgen Schmidhuber](https://people.idsia.ch/) Jürgen Schmidhuber's IDSIA page on recurrent neural networks and LSTM, with history and references. Intermediate learning_resource guide EU-DE en - ### [NYU Deep Learning (LeCun/Canziani)](/foundations/llm-fundamentals/nyu-deep-learning-lecun-canziani/index.md) by [Alfredo Canziani](https://atcold.github.io/) NYU Deep Learning course (Spring 2021) by Yann LeCun and Alfredo Canziani, with lectures, labs and notebooks. Intermediate learning_resource guide West en - ### [OECD AI Recommendation (OECD-LEGAL-0449)](/foundations/llm-fundamentals/oecd-ai-recommendation-oecd-legal-0449/index.md) by [OECD](https://www.oecd.org/) OECD Recommendation of the Council on Artificial Intelligence, the source of the OECD AI Principles and AI system definition. Intermediate learning_resource docs Global en|fr - ### [PDE-Transformer](/foundations/llm-fundamentals/pde-transformer/index.md) by [TUM Physics-based Simulation](https://ge.in.tum.de) PDE-Transformer project page: transformer architecture for learning partial differential equations from data. Intermediate learning_resource guide EU-DE en - ### [Physics-based Deep Learning (TUM)](/foundations/llm-fundamentals/physics-based-deep-learning-tum/index.md) by [Nils Thuerey et al. (TU Munich)](https://physicsbaseddeeplearning.org/) Physics-based Deep Learning book from TUM: hands-on guide to combining physical simulation with deep learning. Intermediate learning_resource guide West en - ### [PointNet](/foundations/llm-fundamentals/pointnet/index.md) by [Charles R. Qi et al. (Stanford University)](https://www.stanford.edu/) PointNet project page: deep network architecture that consumes raw point clouds for 3D classification and segmentation. Intermediate learning_resource guide US en - ### [Roboflow documentation](/foundations/llm-fundamentals/roboflow-documentation/index.md) by [Roboflow](https://roboflow.com/) Roboflow documentation for building computer-vision datasets, training models and deploying them. Intermediate learning_resource docs US en - ### [sktime](/foundations/llm-fundamentals/sktime/index.md) by [sktime](https://sktime.net/) sktime: open-source Python framework for time-series forecasting, classification and anomaly detection. Intermediate learning_resource docs Global en - ### [Soniox Docs: Models](/foundations/llm-fundamentals/soniox-speech-model-registry-and-lifecycle-notes/index.md) by [Soniox](https://soniox.com/) Soniox models page listing speech-to-text model versions, changelog and deprecations. Intermediate learning_resource docs United States; Slovenia en - ### [Speechmatics technical articles](/foundations/llm-fundamentals/speechmatics-technical-articles/index.md) by [Speechmatics](https://speechmatics.com/) Speechmatics articles on speech recognition technology, product news and AI research. Intermediate learning_resource guide UK en - ### [UvA Deep Learning tutorials](/foundations/llm-fundamentals/uva-deep-learning-tutorials/index.md) by [Phillip Lippe (University of Amsterdam)](https://uvadlc.github.io/) University of Amsterdam deep learning tutorial notebooks in PyTorch and JAX/Flax, covering core architectures. Intermediate learning_resource guide West en - ### [XGBoost documentation](/foundations/llm-fundamentals/xgboost-documentation/index.md) by [XGBoost project (DMLC)](https://xgboost.ai/) XGBoost documentation: distributed gradient boosting library with training, GPU support and parameter guides. Intermediate learning_resource docs International en - ### [YSDA Practical Deep Learning](/foundations/llm-fundamentals/ysda-practical-deep-learning/index.md) by [Yandex School of Data Analysis](https://yandexdataschool.com) YSDA Practical_DL GitHub repo: deep learning course materials from Yandex School of Data Analysis, HSE and Skoltech. Intermediate learning_resource course Russia; international en - ### [YSDA Practical RL](/foundations/llm-fundamentals/ysda-practical-rl/index.md) by [Yandex School of Data Analysis](https://yandexdataschool.com) YSDA Practical_RL GitHub repo: open reinforcement-learning course with notebooks and assignments from HSE and YSDA. Intermediate–Advanced learning_resource course Russia en|ru - ### [Zoom Scribe API documentation](/foundations/llm-fundamentals/zoom-scribe-speech-to-text-api-documentation/index.md) by [Zoom](https://www.zoom.com/) Zoom Scribe API documentation: transcription service for many media formats, with modes and authentication details. Intermediate learning_resource docs United States en - ### [Agent57](/foundations/llm-fundamentals/agent57/index.md) by [Adrià Puigdomènech Badia et al. (Google)](https://ai.google/) arXiv paper (2020) introducing Agent57, the first agent to exceed the human baseline on all 57 Atari games. Advanced–Expert learning_resource paper UK en - ### [ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)](/foundations/llm-fundamentals/alexnet-2/index.md) by [Alex Krizhevsky, Ilya Sutskever and Geoffrey E. Hinton (University of Toronto)](https://www.utoronto.ca/) NeurIPS paper (PDF, 2012) AlexNet: ImageNet classification with deep convolutional neural networks. Advanced–Expert learning_resource paper North America — Canada - ### [Faster sorting algorithms discovered using deep reinforcement learning (AlphaDev)](/foundations/llm-fundamentals/alphadev-faster-sorting/index.md) by [Daniel J. Mankowitz et al. (Google DeepMind)](https://deepmind.google/) Nature paper (2023) on AlphaDev discovering faster sorting algorithms with deep RL. Advanced–Expert learning_resource paper West en - ### [Mastering the game of Go with deep neural networks and tree search (AlphaGo)](/foundations/llm-fundamentals/alphago-nature-2016/index.md) by [David Silver et al. (DeepMind)](https://deepmind.google/) Nature paper (2016) on AlphaGo, mastering Go with deep neural networks and tree search. Advanced–Expert learning_resource paper West en - ### [Grandmaster level in StarCraft II using multi-agent reinforcement learning (AlphaStar)](/foundations/llm-fundamentals/alphastar/index.md) by [Oriol Vinyals et al. (DeepMind)](https://deepmind.google/) Nature paper (2019) on AlphaStar reaching grandmaster level in StarCraft II with multi-agent RL. Advanced–Expert learning_resource paper West en - ### [Discovering faster matrix multiplication algorithms with reinforcement learning (AlphaTensor)](/foundations/llm-fundamentals/alphatensor/index.md) by [Alhussein Fawzi et al. (Google DeepMind)](https://deepmind.google/) Nature paper (2022) on AlphaTensor discovering faster matrix multiplication algorithms with RL. Advanced–Expert learning_resource paper West en - ### [AlphaZero](/foundations/llm-fundamentals/alphazero/index.md) by [David Silver et al. (DeepMind)](https://deepmind.google/) arXiv paper (2017) introducing AlphaZero, mastering chess and shogi through self-play reinforcement learning. Advanced–Expert learning_resource paper West en - ### [Chronos: Learning the Language of Time Series](/foundations/llm-fundamentals/chronos-2/index.md) by [Abdul Fatir Ansari et al. (Amazon)](https://www.amazon.science/) arXiv paper (2024) introducing Chronos, pretrained time-series forecasting models using language-model tokenization. Advanced–Expert learning_resource paper Global (Amazon/AWS; US/German en - ### [CLIP](/foundations/llm-fundamentals/clip/index.md) by [Alec Radford et al. (OpenAI)](https://openai.com/) arXiv paper (2021) introducing CLIP, contrastive language-image pretraining for transferable visual models. Advanced learning_resource paper West en - ### [DenseNet](/foundations/llm-fundamentals/densenet/index.md) by [Gao Huang et al. (Cornell University)](https://www.cornell.edu) arXiv paper (2016) "Densely Connected Convolutional Networks", introducing DenseNet, where each layer receives feature maps from all earlier layers. Advanced–Expert learning_resource paper CN en - ### [DETR](/foundations/llm-fundamentals/detr/index.md) by [Nicolas Carion et al. (Meta)](https://ai.meta.com/) arXiv HTML version of the DETR paper (2020) on end-to-end object detection with transformers. Advanced–Expert learning_resource paper US en - ### [DINOv2: Learning Robust Visual Features without Supervision](/foundations/llm-fundamentals/dinov2-2/index.md) by [Maxime Oquab et al. (Meta AI)](https://ai.meta.com/) arXiv HTML version of the DINOv2 paper (2023) on self-supervised visual features. 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