The Best Articles in Machine Learning
The most useful articles in Machine Learning from around the web—beginners to advanced—curated by thought leaders and our community. We focus on timeless pieces and update the list whenever we discover new, must-read articles or videos—make sure to bookmark and revisit this page.
Top 5 Machine Learning Articles
At a glance: these are the articles that have been most read, shared, and saved in Machine Learning by Refind users.
What is ...?
New to Machine Learning? These articles make an excellent introduction.
Free AI for Beginners Course
Microsoft has put together an AI course for beginners, consisting of a 12 week, 24 lesson curriculum, available for free to all.
What is reinforcement learning? How AI trains itself
Reinforcement learning is the subset of ML by which an algorithm can be programmed to respond to complex environments for optimal results.
Learn Julia For Beginners – The Future Programming Language of Data Science and Machine Learning Explained
Julia is a high-level, dynamic programming language, designed to give users the speed of C/C++ while remaining as easy to use as Python. This means that developers can solve problems faster and more…
What is it to be Bayesian? The (pretty simple) math modelling behind a Big Data buzzword
If you’ve ever tripped up over the term ‘Bayesian’ while reading up on data or tech, fear not. Strip away the jargon and notation, and even the mathematics-averse can make sense of the simple yet…
A visual introduction to machine learning
What is machine learning? See how it works with our animated data visualization.
How to ...?
How to Spot a Machine Learning Opportunity, Even If You Aren’t a Data Scientist
What do you want to predict, and do you have the data?
How to learn PyTorch: A resources guide for developers
If you want to learn PyTorch, check out these books, courses, tutorials, videos, and websites about the open source machine learning library.
Trending
These links are currently making the rounds in Machine Learning on Refind.
VALL-E: Microsoft's new zero-shot text-to-speech model can duplicate everyone's voice in three seconds
Since the release of the first text-to-speech (TTS) model, researchers have been looking for ways to improve the way these systems generate speech. The
Large Language Model: world models or surface statistics?
A mystery Large Language Models (LLM) are on fire, capturing public attention by their ability to provide seemingly impressive completions to user prompts (NYT coverage). They are a delicate…
Bayesian statistics and machine learning: How do they differ?
A researcher who would like to remain anonymous writes: My colleagues and I are disagreeing on the differentiation between machine learning and Bayesian statistical approaches. I find them…
imaginAIry/README.md at master
AI imagined images. Pythonic generation of stable diffusion images. - imaginAIry/README.md at master · brycedrennan/imaginAIry
google-research/tuning_playbook: A playbook for systematically maximizing the performance of deep learning models.
A playbook for systematically maximizing the performance of deep learning models. - GitHub - google-research/tuning_playbook: A playbook for systematically maximizing the performance of deep learni...
Short Articles
Short on time? Check out these useful short articles in Machine Learning—all under 10 minutes.
Why data remains the greatest challenge for machine learning projects
Appen’s latest State of AI Report reveals advances in helping enterprises overcome barriers to sourcing and preparing their data.
Machine learning could vastly speed up the search for new metals
It’s a development that could be useful for applications from outer space to the deep sea.
Why Meta’s latest large language model only survived three days online
Galactica was supposed to help scientists. Instead, it mindlessly spat out biased and incorrect nonsense.
Machine Learning Algorithms Explained in Less Than 1 Minute Each
Learn about some of the most well known machine learning algorithms in less than a minute each.
AI: The pattern is not in the data, it's in the machine
No, the patterns computers create are not an inherent property of data, they are an emergent property of the structure of the program itself.
«You might say, a program of this kind doesn't "see" or "perceive" so much as it filters. »
Long Articles
These are some of the most-read long-form articles in Machine Learning.
Are Large Language Models Our Limit Case?
How is it possible to go forward with large language models with the knowledge of just how biased, how incomplete, and how harmful — to both people and the planet — these models truly are?
Intercom on Product: How ChatGPT changed everything
Listen to our Co-founder Des Traynor and Director of Machine Learning Fergal Reid discuss the implications of ChatGPT on tech and customer support.
Machine learning, explained
Machine learning is a powerful form of artificial intelligence that is affecting every industry. Here’s what you need to know about its potential and limitations and how it’s being used.
«Machine learning is a subfield of artificial intelligence that gives computers the ability to learn without explicitly being programmed.»
Deep Learning Is Hitting a Wall
What would it take for artificial intelligence to make real progress?
The Rise of the Transformers: Explaining the Tech Underlying GPT-3
GPT-3 is generating a lot of hype.
Thought Leaders
We monitor hundreds of thought leaders, influencers, and newsletters in Machine Learning, including:
Andrew Ng
Co-Founder of Coursera; Stanford CS adjunct faculty. Former head of Baidu AI Group/Google Brain. #ai #machinelearning, #deeplearning #MOOCs
Hilary Mason
Co-Founder of @HiddenDoorCo. Formerly Founder of @FastForwardLabs (acquired by @Cloudera). I ♥ data and cheeseburgers. She/her.
Demis Hassabis
Founder & CEO @DeepMind @IsomorphicLabs - working on AGI. Trying to understand the fundamental nature of reality
The Gradient (sigmoid.social/@thegradient)
The Gradient cuts through the hype and the cynicism to provide accessible, sophisticated reporting on the latest AI research.
Kirk Borne
@dataprime_ai Data Scientist. Freelancer. Global Speaker. Founder @LeadershipData. Top #BigData #DataScience #AI #IoT #ML Influencer. PhD Astrophysics @Caltech
Publications
We monitor hundreds of publications, blogs, newsletters, and news sources in Machine Learning, including:
MIT Technology Review
Our in-depth reporting on innovation reveals and explains what’s really happening now to help you know what’s coming next. http://technologyreview.com/newsletters
KDnuggets
KD stands for Knowledge Discovery. Covering #DataScience #MachineLearning #AI #Analytics. Edited by @mattmayo13. Founded by Gregory Piatetsky-Shapiro.
Quanta Magazine
Big ideas in science and math. Because you want to know more. Launched by @SimonsFdn. 2022 Pulitzer Prize in Explanatory Reporting. http://quantamagazine.org
OpenAI
OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. We’re hiring: http://openai.com/jobs
MIT Sloan School of Management
Ideas made to matter.
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Every day Refind picks 5 links from around the web for every user, tailored to the user’s interests. Picking only a handful of links means focusing on what’s relevant and useful. We favor timeless pieces—links with long shelf-lives, articles that are still relevant one month, one year, or even ten years from now. These lists of the best resources on any topic are the result of years of careful curation.
How does Refind curate?
It’s a mix of human and algorithmic curation, following a number of steps:
- We monitor 10k+ sources and 1k+ thought leaders on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.
- In addition, our users save links from around the web using our Save buttons and our extensions.
- Our algorithm processes 100k+ new links every day and uses external signals to find the most relevant ones, focusing on timeless pieces.
- Our community of active users gets 5 links every day, tailored to their interests. They provide feedback via implicit and explicit signals: open, read, listen, share, add to reading list, save to «Made me smarter», «More/less like this», etc.
- Our algorithm uses these internal signals to refine the selection.
- In addition, we have expert curators who manually curate niche topics.
The result: lists of the best and most useful articles on hundreds of topics.
How does Refind detect «timeless» pieces?
We focus on pieces with long shelf-lives—not news. We determine «timelessness» via a number of metrics, for example, the consumption pattern of links over time.
How many sources does Refind monitor?
We monitor 10k+ content sources on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.
Which sources does Refind monitor in Machine Learning?
We monitor hundreds of sources in Machine Learning, including MIT Technology Review, KDnuggets, Quanta Magazine, OpenAI, MIT Sloan School of Management, and many more.
Who are the thought leaders in Machine Learning?
We follow dozens of thought leaders in Machine Learning, including Andrew Ng, Hilary Mason, Demis Hassabis, The Gradient (sigmoid.social/@thegradient), Kirk Borne.
Missing a thought leader? Submit them here
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