Top 5 AI Articles of February 2022 Every Data Scientist Should Read

Here are the five best HackerNoon articles related to artificial intelligence in February. I hope they will help you learn more about machine learning this year. Note that the five articles you will see were curated by myself amongst hundred of other super interesting ones that you might enjoy even more. So please feel free to look at the on HackerNoon and keep learning! AI tag And please let me know what you think of this format by liking the video and commenting if you'd like it to become a monthly thing or not in collaboration with Hackernoon! Enjoy! Watch the video References ►The Article: ►5: Reinforcement Learning Course: Part 1 - ►4: Learn K-Means Clustering by Quantizing Color Images in Python - ►3: Using Weights and Biases to Perform Hyperparameter Optimization - ►2: Confusion Matrix in Machine Learning: Everything You Need to Know - ►1: Verified Writers vs. GPT3: Combating Disinformation with the Rise of Robots - ►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/hn-top-5-articles-february/ The Top 5 AI Articles: https://hackernoon.com/reinforcement-learning-course-part-1 https://hackernoon.com/learn-k-means-clustering-by-quantizing-color-images-in-python https://hackernoon.com/using-weights-and-biases-to-perform-hyperparameter-optimization https://hackernoon.com/confusion-matrix-in-machine-learning-everything-you-need-to-know https://hackernoon.com/verified-writers-vs-gpt3-combating-disinformation-with-the-rise-of-robots https://www.louisbouchard.ai/newsletter/ Video Transcript 00:00 if you enjoy my videos but prefer 00:02 reading know that you can also find an 00:04 article version of my videos on hacker 00:06 noon every week i've been sharing them 00:08 there for over a year now and i've even 00:11 had a great time participating in their 00:13 podcast with amy this is why i wanted to 00:15 collaborate with them to make this video 00:17 possible here are the 5 best articles 00:20 related to artificial intelligence in 00:22 february hoping they will make you want 00:25 to learn more and visit their website 00:27 this video is sponsored by hackernoon 00:29 and the five articles you will see were 00:31 curated by myself amongst hundreds of 00:34 other super interesting ones that you 00:36 might enjoy even more so please feel 00:39 free to look at the ai tag on hacker 00:41 noon and keep learning and please let me 00:44 know what you think of this format by 00:46 liking and commenting if you'd like it 00:48 to become a monthly thing or not 00:50 personally i loved going through all the 00:52 articles and finding these five gems to 00:54 share with you but first i think you 00:56 shall know a bit more about hacker noon 00:58 and why i like them hacker noon is the 01:00 best place for software developers 01:02 blockchain experts data scientists and 01:04 tech people like us to read write and 01:07 even publish indeed just like me you can 01:10 also publish your own work on there for 01:13 free getting published on hacker noon 01:15 gives you third party validation for 01:16 your writing and puts you alongside 01:18 engineers from the top tech companies 01:21 who have also chosen to write on 01:22 hackernoon giving you great visibility 01:25 in your niche and they will help spread 01:26 your articles on twitter and other media 01:29 which helped me quite a lot 01:32 this first article is incredible it won 01:35 the fifth position simply because it 01:37 isn't really an article but a complete 01:39 course paul labarta barrow did a 01:41 fantastic job explaining reinforcement 01:44 learning in this part one of his 01:45 articles series aiming to cover the 01:48 fundamentals up to cutting-edge 01:50 techniques used in reinforcement 01:51 learning she walks you through a clear 01:53 step-by-step course with coding examples 01:56 and tutorials in python you have the 01:58 theory analogies examples code and jokes 02:01 he even provides homeworks and his email 02:04 address to reach out if needed it's 02:06 beautifully explained and a pretty good 02:08 resource if you'd like to get into 02:09 reinforcement learning and it's entirely 02:12 free 02:14 the fourth position goes to bala priya 02:16 with her article called learn key means 02:18 clustering by quantizing color images in 02:21 python in this article bella covers a 02:24 wide range of subjects such as 02:25 supervised learning versus unsupervised 02:27 learning the k-means algorithm the elbow 02:30 method and a clear example explaining 02:32 these concepts using color quantization 02:34 she is a fantastic writer and teacher 02:37 and even comes back later in this top 02:39 five having learned k-means with the 02:42 same example is the best way to 02:43 visualize and graphs how it works she 02:46 provides clear explanations of the math 02:48 and code behind the algorithms great 02:50 visuals and even code for you to 02:52 implement it as well if you are not 02:54 familiar with k-means or color 02:56 quantization you should definitely read 02:58 more this algorithm is widely used and 03:01 pretty powerful you will love it and 03:03 it's pretty fun to play with the images 03:05 you generate using the algorithm 03:09 yes this is an article about weights and 03:12 biases and it isn't even sponsored this 03:14 is because i simply love their tool and 03:17 so does codcam the authors of this 03:20 article they cover how to perform hyper 03:22 parameter optimization using weights and 03:25 biases since i already speak a lot about 03:27 weights and biases in my other videos i 03:29 won't enter into the details here but 03:31 this is a fantastic article if you'd 03:33 like to improve your weights and biases 03:35 skills and have a clear guide to set 03:37 your optimization process easily it has 03:40 a clear code example and a great 03:42 explanation of hyper parameter 03:43 optimizations different approaches and 03:46 tools check this one out if you use 03:48 weights and biases to track your 03:50 experiments 03:52 confusion mattresses are extremely 03:54 useful for evaluating the performance of 03:56 your machine learning models in this 03:58 great article bella priya once again 04:01 provides a fantastic explanation this 04:04 time covers what a confusion matrix is 04:07 why to use it and when to do so the 04:09 whole tutorial is extremely clear with 04:11 everything you need to follow along she 04:13 also includes an overview of machine 04:15 learning and classification tasks as she 04:17 highlights this tutorial will help you 04:20 understand the confusion matrix and the 04:22 various matrix that you can calculate 04:25 from the confusion matrix so if you work 04:27 with classification models or are 04:29 starting your way in machine learning 04:31 this is a must read 04:33 and my favorite article of the month is 04:36 verified writers versus gpt3 combating 04:39 this information with the rise of robots 04:42 in this article sarah ottman from the 04:45 non-profit organization verified writers 04:48 covers a side of gpt3 that isn't 04:50 discussed enough the dangers of having 04:53 access to such a great language model 04:55 she covers what gpt3 is its risks the 04:58 dangers of fake news and why a good ai 05:02 may be dangerous for writers and the 05:04 population the latter is also the reason 05:07 openai used to explain why they license 05:10 the usage of dpt3 instead of open 05:12 sourcing it i think there may be other 05:14 reasons for that but hey who knows the 05:16 article is interesting and well written 05:19 hopefully not by gpt3 it even provides 05:22 tool too as she says address the rise of 05:25 robots and protect human writers this 05:27 last one is my favorite due to its 05:29 discussion of ai ethics if ai ethics 05:32 also interests you you should definitely 05:35 read this piece also i'd strongly invite 05:37 you to follow my newsletter where two 05:39 amazing people work with me to share 05:41 opinions and knowledge about the ethical 05:43 side of the papers i cover here on the 05:45 channel in this week's iteration martina 05:48 extends on this last article with a very 05:50 interesting view the link is in the 05:52 description if you'd like to learn more 05:54 and subscribe to it thank you hackernoon 05:56 for sponsoring the video and a special 05:58 thanks to you that are still watching i 06:01 hope you enjoyed this special video and 06:03 don't forget to subscribe to learn more 06:05 about ai stay up to date with new 06:07 research and support the channel please 06:09 let me know what you think of this 06:11 format in the comments and leave a like 06:13 if you'd like it to become a monthly 06:15 thing or not before you leave don't 06:17 forget that you have until the end of 06:19 march to participate in the nvidia rtx 06:21 3080ti gpu giveaway in my previous video 06:25 where you can find all the details 06:27 i will see you next week with another 06:29 awesome paper covered

Top 5 AI Articles of February 2022 Every Data Scientist Should Read

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