Home Lists


Keep in mind, anything that is bolded means that I either enjoy consuming the content or I always consume it, italic means I lost interest a long time ago but you might like it, and no text-styling means that it is on my radar.

Newsletter list


  • Hacker News Digest: Best way to know about the top things in tech every week.
  • KDnuggets News: Shares top articles about Data Science every other day.
  • The Batch: Presents the most important AI events and perspective in a curated, easy-to-read report for engineers and business leaders every Wednesday.


  • The Pragmatic Engineer: The #1 technology newsletter on Substack. Highly relevant for software engineers and engineering managers, useful for those working in tech. Written by engineering manager and software engineer Gergely Orosz who was previously at Uber, Skype/Microsoft, and at high-growth startups.
  • ByteByteGo: A popular weekly newsletter covering topics and trends in large-scale system design, from the authors of the best-selling System Design Interview series.
  • arjan_codes: Arjan shares some useful tips and tricks for Python developers and best Software Engineering practices.

Deep Learning Research

  • The Gradient: The Gradient is an organization is an organization with the missions of making it easier for anyone to learn about AI and of facilitating discussion within the AI community.
  • Davis Summarizes Papers: David goes through all of 600 new machine learning papers submitted to arXiv and identifies 10-20 that he thinks are especially interesting, practical, or promising. He then writes a summary of each one, often with some commentary.
  • Deep (Learning) Focus: Deep (Learning) Focus is a newsletter that releases twice a week that focuses on research in deep learning and artificial intelligence.
  • TheSequence: TheSequence is an ML community media, trusted by over 144,000+ specialists from all over the world, including the top AI labs like DeepMind, OpenAI, Google Brain, MSFT Research, LinkedIn, universities like MIT, Cornell, Berkeley, Carnegie Mellon, Columbia, and hundreds of large enterprises.


  • Eleanor Konik: Eleanor Konik shares relevant updates, cool plugins, and many things in regard to Obsidian, Person Knowledgebase System (PKM), and writing.

Podcast list


  • The Joe Rogan Experience: The official podcast of comedian Joe Rogan.
  • Lex Fridman Podcast: Conversations about AI, science, technology, history, philosophy and the nature of intelligence, consciousness, love, and power. Formerly called the Artificial Intelligence (AI) podcast. Lex is an AI researcher at MIT and beyond.


  • WeAreNetflix: Netflix employees talking about work and life at Netflix, hosted by Netflix Senior Software Engineer Lyle Troxell.
  • Software Engineering Daily: Technical interviews about software topics.
  • Programming Throwdown: Programming Throwdown attempts to educate Computer Scientsts and Software Engineers on a cavalcade of programming and tech topics. Every show covers a new programming language, so listeners will be able to speak intelligently about any programming language.

Data Science

  • Data Skeptic: Data Skeptic is your source for a perspective of scientific skepticism on topics in statistics, machine learning, big data, artificial intelligence, and data science. Our weekly podcast and blog bring you stories and tutorials to help understand our data-driven world.

Deep Learning Research

  • The Gradient: The Gradient is an organization is an organization with the missions of making it easier for anyone to learn about AI and of facilitating discussion within the AI community.
  • Machine Learning Street Talk: Tim Scarfe (Machine Learning Dojo), Connor Shorten (Henry AI Labs), and Yannic Kilcher talk about the latest and greatest in AI every week.
  • The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence): Sam interviews people who are working in industry and academia. Great resource to be aware of what’s happening in the world and how smart people solve them.
  • Underrated ML: Sharing various Machine Learning papers that just haven’t got the love and attention they deserve.

Visual content (e.g. YouTube, Venmo, etc.) and blog lists

I am working on it.

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