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 AI tag on HackerNoon and keep learning!

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!

►The Article: https://www.louisbouchard.ai/hn-top-5-articles-february/

The Top 5 AI Articles:

►5: Reinforcement Learning Course: Part 1 - https://hackernoon.com/reinforcement-learning-course-part-1

►4: Learn K-Means Clustering by Quantizing Color Images in Python -
https://hackernoon.com/learn-k-means-clustering-by-quantizing-color-images-in-python

►3: Using Weights and Biases to Perform Hyperparameter Optimization -
https://hackernoon.com/using-weights-and-biases-to-perform-hyperparameter-optimization

►2: Confusion Matrix in Machine Learning: Everything You Need to Know -
https://hackernoon.com/confusion-matrix-in-machine-learning-everything-you-need-to-know

►1: Verified Writers vs. GPT3: Combating Disinformation with the Rise of
Robots - https://hackernoon.com/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/newsletter/

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if you enjoy my videos but prefer

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reading know that you can also find an

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article version of my videos on hacker

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noon every week i've been sharing them

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there for over a year now and i've even

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had a great time participating in their

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podcast with amy this is why i wanted to

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collaborate with them to make this video

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possible here are the 5 best articles

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related to artificial intelligence in

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february hoping they will make you want

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to learn more and visit their website

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this video is sponsored by hackernoon

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and the five articles you will see were

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curated by myself amongst hundreds of

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other super interesting ones that you

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might enjoy even more so please feel

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free to look at the ai tag on hacker

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noon and keep learning and please let me

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know what you think of this format by

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liking and commenting if you'd like it

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to become a monthly thing or not

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personally i loved going through all the

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articles and finding these five gems to

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share with you but first i think you

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shall know a bit more about hacker noon

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and why i like them hacker noon is the

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best place for software developers

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blockchain experts data scientists and

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tech people like us to read write and

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even publish indeed just like me you can

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also publish your own work on there for

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free getting published on hacker noon

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gives you third party validation for

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your writing and puts you alongside

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engineers from the top tech companies

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who have also chosen to write on

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hackernoon giving you great visibility

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in your niche and they will help spread

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your articles on twitter and other media

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which helped me quite a lot

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this first article is incredible it won

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the fifth position simply because it

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isn't really an article but a complete

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course paul labarta barrow did a

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fantastic job explaining reinforcement

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learning in this part one of his

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articles series aiming to cover the

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fundamentals up to cutting-edge

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techniques used in reinforcement

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learning she walks you through a clear

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step-by-step course with coding examples

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and tutorials in python you have the

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theory analogies examples code and jokes

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he even provides homeworks and his email

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address to reach out if needed it's

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beautifully explained and a pretty good

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resource if you'd like to get into

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reinforcement learning and it's entirely

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free

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the fourth position goes to bala priya

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with her article called learn key means

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clustering by quantizing color images in

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python in this article bella covers a

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wide range of subjects such as

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supervised learning versus unsupervised

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learning the k-means algorithm the elbow

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method and a clear example explaining

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these concepts using color quantization

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she is a fantastic writer and teacher

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and even comes back later in this top

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five having learned k-means with the

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same example is the best way to

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visualize and graphs how it works she

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provides clear explanations of the math

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and code behind the algorithms great

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visuals and even code for you to

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implement it as well if you are not

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familiar with k-means or color

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quantization you should definitely read

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more this algorithm is widely used and

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pretty powerful you will love it and

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it's pretty fun to play with the images

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you generate using the algorithm

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yes this is an article about weights and

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biases and it isn't even sponsored this

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is because i simply love their tool and

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so does codcam the authors of this

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article they cover how to perform hyper

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parameter optimization using weights and

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biases since i already speak a lot about

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weights and biases in my other videos i

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won't enter into the details here but

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this is a fantastic article if you'd

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like to improve your weights and biases

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skills and have a clear guide to set

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your optimization process easily it has

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a clear code example and a great

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explanation of hyper parameter

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optimizations different approaches and

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tools check this one out if you use

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weights and biases to track your

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experiments

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confusion mattresses are extremely

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useful for evaluating the performance of

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your machine learning models in this

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great article bella priya once again

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provides a fantastic explanation this

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time covers what a confusion matrix is

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why to use it and when to do so the

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whole tutorial is extremely clear with

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everything you need to follow along she

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also includes an overview of machine

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learning and classification tasks as she

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highlights this tutorial will help you

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understand the confusion matrix and the

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various matrix that you can calculate

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from the confusion matrix so if you work

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with classification models or are

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starting your way in machine learning

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this is a must read

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and my favorite article of the month is

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verified writers versus gpt3 combating

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this information with the rise of robots

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in this article sarah ottman from the

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non-profit organization verified writers

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covers a side of gpt3 that isn't

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discussed enough the dangers of having

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access to such a great language model

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she covers what gpt3 is its risks the

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dangers of fake news and why a good ai

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may be dangerous for writers and the

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population the latter is also the reason

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openai used to explain why they license

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the usage of dpt3 instead of open

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sourcing it i think there may be other

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reasons for that but hey who knows the

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article is interesting and well written

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hopefully not by gpt3 it even provides

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tool too as she says address the rise of

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robots and protect human writers this

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last one is my favorite due to its

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discussion of ai ethics if ai ethics

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also interests you you should definitely

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read this piece also i'd strongly invite

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you to follow my newsletter where two

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amazing people work with me to share

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opinions and knowledge about the ethical

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side of the papers i cover here on the

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channel in this week's iteration martina

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extends on this last article with a very

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interesting view the link is in the

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description if you'd like to learn more

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and subscribe to it thank you hackernoon

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for sponsoring the video and a special

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thanks to you that are still watching i

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hope you enjoyed this special video and

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don't forget to subscribe to learn more

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about ai stay up to date with new

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format in the comments and leave a like

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thing or not before you leave don't

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forget that you have until the end of

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i will see you next week with another

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awesome paper covered