Ecosyste.ms: Awesome
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ai-links
This is the list of links on Deep Learning that I have collected over time and still collecting.
https://github.com/khushmeeet/ai-links
Last synced: 3 days ago
JSON representation
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Resources
- An introduction to Generative Adversarial Networks (with code in TensorFlow) - AYLIEN News API
- Generative Models
- Adverarial Nets
- Generative Adversarial Nets in TensorFlow - Agustinus Kristiadi
- A (Very) Gentle Introduction to Generative Adversarial Networks (a.k…
- Eric Jang: Generative Adversarial Nets in TensorFlow (Part I)
- Generative Adversarial Networks Explained with a Classic Spongebob Squarepants Episode | by Arthur Juliani | Medium
- YouTube - Active One-shot Learning
- 1605.06065 One-shot Learning with Memory-Augmented Neural Networks
- Differential neural computer from DeepMind and more advances in backward propagation
- Variational Autoencoders Explained
- Under the Hood of the Variational Autoencoder (in Prose and Code)
- Variational Autoencoder in TensorFlow
- Eric Jang: Tutorial: Categorical Variational Autoencoders using Gumbel-Softmax
- Variational Autoencoder (VAE) in Pytorch - Agustinus Kristiadi
- 1602.05568 Multi-layer Representation Learning for Medical Concepts
- 1605.03481 Tweet2Vec: Character-Based Distributed Representations for Social Media
- Machine Learning Crash Course | Google Developers
- Stanford CRFM
- HuBERT: How to Apply BERT to Speech, Visually Explained | Jonathan Bgn
- Python Numpy Tutorial (with Jupyter and Colab)
- 1603.07012 Semi-supervised Word Sense Disambiguation with Neural Models
- 1708.00524 Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm
- 1704.08847 Parseval Networks: Improving Robustness to Adversarial Examples
- SoundNet: Learning Sound Representations from Unlabeled Video - MIT
- DeepMoji
- Introduction to Machine Learning Interviews Book · MLIB
- Schedule « AGI-21: SF Bay Area and Virtual, Oct. 15-18, 2021
- 2022 AGI Safety Fundamentals alignment curriculum
- Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
- Deep Learning Links
- MLExpert | MLExpert - land your dream Machine Learning job
- Cloudera Fast Forward Blog
- Design Patterns in Machine Learning Code and Systems
- The Illustrated Machine Learning Website
- Google’s DeepMind AI Now Capable of ‘Deep Neural Reasoning’ – The New Stack
- Tutorial - What is a variational autoencoder? – Jaan Altosaar
- Implementing Dynamic memory networks · YerevaNN
- PyTorch quick start: Classifying an image — Outcome Blog documentation
- Stanford DAWN · DAWN
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Deep Learning Repositories
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Interpretability
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Publications, Annotations and Visualizations
- A Mathematical Framework for Transformer Circuits
- Transformers from Scratch
- The Illustrated Retrieval Transformer – Jay Alammar – Visualizing machine learning one concept at a time.
- The Annotated Transformer
- Logistic Regression
- Attention, Transformers, in Neural Network Large Language Models
- Transformer Circuits
- Transformers from Scratch
- You don’t know JAX
- The Illustrated Stable Diffusion – Jay Alammar – Visualizing machine learning one concept at a time.
- CS 221 ― Artificial Intelligence - Cheat Sheets
- Differentiable Programming from Scratch – Max Slater – Computer Graphics, Programming, and Math
- Algebra, Topology, Differential Calculus, and Optimization Theory For Computer Science and Machine Learning - PDF
- OpenAI Microscope
- A Visual Guide to Vision Transformers
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Publications and Annotations
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Courses
- Natural Language Processing (NLP) for Semantic Search | Pinecone
- Syllabus for Mathematical Background for Machine Learning
- Deep Learning for Natural Language Processing
- Stanford CS 224N | Natural Language Processing with Deep Learning
- A visual introduction to machine learning
- Neural networks and deep learning
- AMMI Geometric Deep Learning Course - Second Edition (2022) - YouTube
- First Principles of Computer Vision - YouTube
- Deep Learning Systems
- Home - Made With ML
- Cornell CS4780 - Machine Learning for Intelligent Systems
- “Crash Course” - ML@B Blog Berkeley
- Natural Language Processing Demystified
- Deep Learning Fundamentals - Lightning AI
- TinyML and Efficient Deep Learning Computing
- Deep Learning for Particle Physicists — Deep Learning for Particle Physicists
- UNIGE 14x050 – Deep Learning
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