AI
Artificial intelligence: machine learning, neural networks, large language models, deep learning, AI research, and AI tools.
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Bonnard bonnard.dev
Governed, multi-tenant MCP access to your customers' data. Turn your warehouse, dbt, or semantic layer into a secure, per-customer MCP for AI agents.
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AI for Database aifordatabase.com
Agentic AI platform to connect any database (PostgreSQL, MySQL, MongoDB, etc.) and query in plain English; includes self-refreshing intelligent dashboards and action workflows triggered by data changes.
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Gregory Valiant. The Modern Algorithmic Toolbox. Stanford web.stanford.edu
It covers hashing, dimension reduction, linear and convex programming, gradient descent and regression, sampling and estimation, compressive sensing, linear-algebraic techniques (principal components analysis, singular value decomposition, spectral techniques), and an intro to…
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Mary Wootters. Randomized Algorithms and Probabilistic Analysis. Stanford web.stanford.edu
Key tools of probabilistic analysis, and application of these tools to understand the behaviors of random processes and algorithms. Emphasis is on theoretical foundations, though applications will be discussed in machine learning and data analysis, networking, and systems…
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Simons' Institute simons.berkeley.edu
Programs, Events, and workshops, that aim toward maximizing impact and engagement across the theoretical computer science community.
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Moitra. Theoretical Foundations for Deep Learning. MIT people.csail.mit.edu
It explores theoretical foundations for deep learning, emphasizing the following themes: (1) Approximation: What sorts of functions can be represented by deep networks, and does depth provably increase the expressive power? (2) Optimization: Essentially all optimization…
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Telgarsky. Deep Learning Theory. Illinois mjt.cs.illinois.edu
Focuses on simplified proofs over what appears in the literature, and classical perspective of achieving a low test error for binary classification with IID data via standard (typically ReLU) feedforward networks.
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Vazirani & Kearns. An Introduction to Computational Learning Theory mitpress.mit.edu
Emphasizing issues of computational efficiency, It introduces a number of central topics in computational learning theory.
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Vaughan. CS260: Machine Learning Theory jennwv.com
A broad overview of the theoretical foundations underlying common machine learning algorithms.
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Blum. An Introduction to the Theory of Machine Learning. TTIC home.ttic.edu
The basic theory underlying machine learning and the process of generalizing from data.
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Xu. Topics in Learning and Game Theory haifeng-xu.com
A graduate level course covering topics at the interface between machine learning and game theory.
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Fang. Advanced Topics in Machine Learning and Game Theory feifang.info
A graduate-level course covering the topics at the intersection of machine learning and game theory.
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Theory Announcements dmatheorynet.blogspot.com
DMANET spreads information on conferences, workshops, seminars etc. relating to discrete mathematics and algorithms.
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Agrawal & Jaiswal. When Machine Learning Meets AI and Game Theory cs229.stanford.edu
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Livni. COS 511 Theoretical Machine Learning. Princeton cs.princeton.edu
Formally define and study various models that have been proposed for learning. The course will present and contrast the statistical, computational and online models for learning. We will present and rigorously analyze some of the most successful algorithms in machine learning…
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Arora. Overcoming Intractability in Machine Learning cs.princeton.edu
A seminar course that will focus on the following phenomenon: many problems in machine learning are formally intractable (e.g., NP-hard). Nevertheless they are solved in practice by heuristics. Can we design algorithms with provable guarantees (running time, solution quality)?
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Arora. The Computational Universe cs.princeton.edu
Takes us on a broad sweep of scientific knowledge and related technologies: propositional logic of the ancient Greeks (microprocessors); quantum mechanics (silicon chips); network and system phenomena (internet and search engines); computational intractability (secure…
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Arora. Thinking Like a Theorist. Princeton cs.princeton.edu
It covers a large number of the math/CS topics that you need to know for reading and doing research in Computer Science Theory.
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Blum. Intro Machine Learning Theory cs.cmu.edu
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Shalev-Shwartz. Understanding Machine Learning: From Theory to Algorithms cambridge.org
It provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms.
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TensorFlow.js: ML for the web and beyond youtube.com
TensorFlow Dev Summit 2020.
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Official TensorFlow.js video series youtube.com
The YouTube content focuses on TensorFlow ecosystem updates.
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Aaron Ma x.com
World's youngest TensorFlow contributor!
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Nikhil Thorat twitter.com
Co-lead of TensorFlow.js.
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Laurence Moroney twitter.com
Lead of AI Developer Relations at Google.
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Jason Mayes twitter.com
Developer advocate for TensorFlow.js.
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Daniel Smilkov twitter.com
Co-creator of TensorFlow.js.
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Sandeep Gupta twitter.com
Product Manager for TensorFlow.
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Gant Laborde twitter.com
Web & Machine Learning GDE.
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Paige Bailey twitter.com
Building Google AI for everyone, and for every platform.
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Official tfjs models on TensorFlow.js website tensorflow.org
Explore pre-trained TensorFlow.js models that can be used in any project out of the box.
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Official tfjs demo website tensorflow.org
See examples and live demos built with TensorFlow.js!
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@tensorflow-models on NPM npmjs.com
Various pretrained models for TensorFlow.js on NPM.
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Deep Learning with JavaScript manning.com
Learn to use TensorFlow.js to build deep learning models that run directly in the browser, master all the basics of deep learning and explore advanced concepts, like retraining existing models for transfer learning and image generation by Shanqing Cai, Stanley Bileschi, Eric D…
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Glitch glitch.com
Build fast, full-stack web apps in browser for free (Tensorflow.js templates).
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TensorFlow.js gallery github.com
A collection of TensorFlow.js projects, tutorials, videos, and more.
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Effective TensorFlow.js effectivemachinelearning.com
TensorFlow.js tutorials and best practices.
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Machine Learning Crash Course developers.google.com
Google's fast-paced, practical introduction to machine learning.
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Official TensorFlow.js blog blog.tensorflow.org
Covers building models in JavaScript and using them in the browser or in Node.js.
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JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training arxiv.org
The experimental results show that training a neural network in distributed web browsers is feasible and accurate, has a high scalability, and it is an interesting area for research.
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TensorFlow.js: Machine Learning for the Web and Beyond arxiv.org
This paper describes the design, API, and implementation of TensorFlow.js, and highlights some of the impactful use cases.
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Practical Machine Learning in JavaScript apress.com
TensorFlow.js for Web Developers by Charlie Gerard.
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Practical TensorFlow.js apress.com
Deep Learning in Web App Development by Juan De Dios Santos Rivera.
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Hands-On Machine Learning with TensorFlow.js amazon.com
A guide to building ML applications integrated with web technology using the TensorFlow.js library by Kai Sasaki.
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AiJS aijs.rocks
A curated collection of inspirational AI-powered JavaScript apps.
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Beginning ML with TensorFlow.js academy.infinite.red
Full online course for web devs to get into TF.js.
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You.com you.com
A search engine built on AI that provides users with a customized search experience while keeping their data 100% private.
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ChatGPT Heralds an Intellectual Revolution wsj.com
An op-ed by Henry Kissinger, Eric Schmidt and Daniel Huttenlocher. Wall Street Journal, February 24, 2023.
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ChatSonic writesonic.com
An AI-powered assistant that enables text and image creation.
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