Top 5 Machine Learning Blogs To Follow!

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Top 5 Machine Learning Blogs To Follow!

AssemblyAI 02.03.2022 1 937 просмотров 99 лайков

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In this video we’ve compiled the top 5 Machine Learning blogs that our team at AssemblyAI likes to follow. These blogs are also great resources for ML beginners, as they offer excellent foundational content as well! Get your Free Token for AssemblyAI Speech-To-Text API 👇https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_pat_18 Blogs: https://distill.pub https://machinelearningmastery.com/blog/ https://blog.ml.cmu.edu https://neptune.ai/blog https://news.ycombinator.com https://paperswithcode.com https://www.assemblyai.com/blog ▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬ 🖥️ Website: https://www.assemblyai.com 🐦 Twitter: https://twitter.com/AssemblyAI 🦾 Discord: https://discord.gg/Cd8MyVJAXd ▶️ Subscribe: https://www.youtube.com/c/AssemblyAI?sub_confirmation=1 🔥 We're hiring! Check our open roles: https://www.assemblyai.com/careers ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #MachineLearning #DeepLearning

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Intro

machine learning and deep learning are constantly evolving every couple of weeks there can be a new paper with a new breakthrough idea that's why it's super important to keep up with all the latest changes and one great way to do this is by following blog posts so in this video we've compiled the top five machine learning blocks that our team at assembly ai likes to follow these blocks are also great for beginners because some of them also offer a lot of foundational content so this list is not exhaustive and i would be very happy if you leave a comment and let us know what's your favorite machine learning block and now without further ado let's get started

Distil

distill is an online research journal that presents itself as an alternative to academic publications it's made by many of the world's most famous ai researchers the content on the website is sorted by peer-reviewed threat commentary and editorial depending on your interest its peer-reviewed articles are registered with the library of congress and crossref and appear in google scholar and what makes distil particular unique is its use of interactive media to distill the latest findings in machine learning one cool article you can check out for example is the understanding convolutions on graphs article

Machine Learning Mastery

article machine learning mastery is less suited to read about the latest academic research but it offers a lot of practical hands-on tutorials aimed at developers it was founded by jason brownlee who holds a phd in artificial intelligence but blog posts are also written by many guest authors the topics include machine learning deep learning computer vision time series nlp lstms algorithms python imbalance learning data preparation and much more

MLCMCU

mlcmu is a dedicated machine learning block from the carnegie mellon university the goal of the blog is to provide content that is accessible to a diverse audience from the general public to advanced researchers they provide bi-weekly publications that are written by cmu students postdocs and faculty and often include findings from academic research performed at the university

Neptune

the neptune block was created for research and production teams that need to run frequent experiments in addition to the blog content neptune provides a tool that helps developers perform experiment tracking and model registry so the block also has a focus on these areas it offers a lot of insightful information across machine learning experiment tracking model management ml ops and ml tools

Hacker News

this one might surprise you because it's not really a block and it's also not really specific to machine learning only hacker news which is run by y combinator is a social website a bit similar to reddit while it's not an exclusive machine learning resource hacker news still houses a lot of great machine learning content for users to sift through other users can upvote content and comment to rank articles and increase visibility or simply use the search function to search for particular machine learning content so this can indeed be used to find trending new machine learning articles

Papers with Code

now we are already done with the five blocks i mentioned but there's one more site which is my personal favorite papers with code allows you to search through trending ml topics and then can see the paper plus the corresponding open source code on github this is just awesome to fully understand the topic play around and test the code for yourself and even build your own projects on top of it you can also click on this browse through state of the art and then find papers with the best benchmarks in the chosen category papers with code is a self-contained team within facebook or now meta all content on this website is openly licensed under this license which is by the way the same that wikipedia uses and everyone can contribute

Honorable Mention

now before i let you go there's one more honorable mention that i'd like to show you and this is our very own assembly ai blog where we produce weekly content for you our blog posts can be paper reviews of state of the art nlp papers fun coding projects or extensive guides and machine learning tutorials for a broader audience so go and check it out and as always if you enjoyed this video then please leave us a thumbs up and then i hope to see you in the next video bye

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