We have a list of resources that we regularly rely on for information on Artificial Intelligence (AI), Machine Learning (ML) & Data Science. This list is a combination of where the different teams in SUPA go to find the best and most trustworthy AI, ML & Data Science knowledge.
So, we decided to share it in hopes that it gives you just as much value as it did for us. Happy reading! Note: The resources shared below are not ranked in any particular order.
AI Time Journal promotes AI initiatives and organizations with the aim to enable people with the knowledge and the tools to drive change and have an impact through AI. Many of the articles published in the journal are contributed by data scientists, domain experts, and company founders.
The Berkeley Artificial Intelligence Research (BAIR) Blog provides an accessible, general-audience medium for Berkeley’s researchers to communicate research findings, perspectives on the field, and various updates. Posts are written by students, post-docs, and faculty in BAIR.
A tech blog that covers a wide range of tech-related topics, mostly geared towards developers and engineers. Stories and articles are from 7,000+ contributing writers.
MIT Technology Review is a magazine wholly owned by the Massachusetts Institute of Technology however it’s editorially independent of the university. They provide insight, analysis, reviews, interviews and live events that explain the newest technologies and their commercial, social, and political impacts.
The joint effort of Google AI, OpenAI, DeepMind, YC Research, and others, Distill is an open science journal and ecosystem supporting the human understanding of machine learning. You’ll find visually appealing and clear explanations of machine learning concepts using modern web technologies.
A computer science portal, created to provide well written, well thought, and well-explained solutions for questions surrounding from programming, algorithm to interviews.
Unite.ai was designed to offer detailed analysis and news on the latest advancements in machine learning and AI technology. It also serves as a platform to highlight new and upcoming AI companies who may not be getting the recognition that they deserve from mainstream media.
Information age started as a print magazine and is now a leading site for the latest news, analysis, guidance, and research on AI for the CTO community.
KDnuggets is a leading site on AI, Analytics, Big Data, Data Mining, Data Science, and Machine Learning, edited by Data Scientist Gregory Piatetsky-Shapiro and Machine Learning Researcher, Matthew Mayo. You may also follow them both on LinkedIn to get first-hand updates on the industry.
One of the industry’s most popular online resources for data practitioners. From Statistics, Analytics to Machine Learning to AI, Data Science Central provides a community experience that includes a rich editorial platform, social interaction, forum-based support, plus the latest information on technology, tools, trends, and careers.
The notable Medium publication is run by an international team of 15 people from diverse backgrounds; from developers to data scientists who review the submissions from writers across the world and provide feedback before publishing them. Their goal is to present well-written, informative Data Science articles.
Analytics Vidhya provides a community-based knowledge portal that hosts Q&A forums, training programs, and publishes Data Science articles for Analytics and Data Science professionals. The site’s main aim is to create the next-gen data science ecosystem.
One of the oldest Data Science blogs on the internet founded by Ryan Swanstrom who was transitioning from a career in software engineering to a career in Data Science in 2012. It began as a way for Swanstrom to share some of the things he has learned along his Data Science journey. You’ll find various resources from data science papers to articles and news.
The world’s largest Data Science community with powerful tools and resources to help you achieve your Data Science goals.
There are also a number of well-known organizations, many of which are leading the development and adoption of AI in their respective industries. Most of them have their own blogs that discuss their progress and research in AI, Machine Learning and Data Science. Here are some of our favourites:
You can spend hours on Reddit where you can gain insights through just reading the threads or engaging in one of the many discussions that take place daily.
It’s a friendly environment that welcomes people regardless of their years of experience in the field. While the format is definitely not as digestible as an article may be, Reddit gives you a more interactive environment where you can ask questions openly and expect a variety of answers.
Quora has over time become a great resource for AI and Machine Learning, especially if you have a burning question to ask. Many top researchers are known to have answered questions on the site. We’ve listed the main AI-related topics, which you can subscribe to
Medium is an online publishing platform for writers and thought leaders in the field to contribute their piece to various publications on. We’ve identified a couple of leading Medium Publications on AI, ML and Data Science as listed below:
Learn more about different data labeling use cases.
Everything from uploading data to seeing it labeled in real time was really cool. This is just way simpler to use compared to Amazon Sagemaker and LabelBox. I was also very impressed with how the platform delivered exactly what we needed in terms of label quality.
I was also able to view the labels as they were being generated, which gave me quick feedback about the label quality, rather than waiting for the whole batch. This replaced my standard manual QA process using external tools like Voxel's Fiftyone, as the labels were clear and easy to parse through in real-time.