after a short summer pause, the new DSB is here! Hopefully you survived Friday the 13th and now you can start reading! I would recommend two articles, one from Analytical about the difference between NLP and NLU. And an article from Business and Career that explains why it’s important to meet in the office and not stay at home all the time.
As always, enjoy your reading.
https://thegradient.pub/machine-learning-wont-solve-the-natural-language-understanding-challenge/ – Very interesting article about the differences between NLP and NLU and why ML is failing in natural language understanding.
https://towardsdatascience.com/deep-learning-for-projectile-trajectory-modeling-fb6380e06b8f – Explanation of paper about generation of additional data in order to train a data-starved neural network for launching of non-rigid objects. (rcmd by reader)
– Go deep into the aggregation functions in PostgreSQL and see what is happening behind the scene.
Computer Science & Science
https://github.blog/2021-08-11-githubs-engineering-team-moved-codespaces/ – GitHub is using Codespaces as the default dev environment.
https://pythonspeed.com/articles/numpy-memory-views/ – Working with memory in NumPy.
https://realpython.com/python-walrus-operator/ – Walrus operator, what is it and how does it work in Python?
Graphs and Visualizations
https://www.visualcapitalist.com/mapped-gdp-per-capita-worldwide/ – Simple vizualizations or a map to be precise with GDP per capita around the world in 2021.
https://matplotlib.org/matplotblog/posts/python-graph-gallery.com/ – I like these galleries – when you need to create a beautiful graph, just go there and you get everything you need. This one is for Python and it’s well known, it was already mentioned in DSB #20. So it’s a reminder. (rcmd by reader)
https://octo.github.com/projects/repo-visualization – Automatic visualization of a GitHub repo and its benefits if you use it.
Business and Career
https://www.theguardian.com/science/2021/jun/03/the-empty-office-what-we-lose-when-we-work-from-home – Thanks to the home office we are missing more than we think.
https://medium.com/predict/how-to-build-an-ai-unicorn-in-6-years-87b7967e1ac1 – Story of a founder of Tractable, AI unicorn, which is a company worth $1 billion. From zero to hero in 6 years.
https://hbr.org/2021/08/stablecoins-and-the-future-of-money – Will stablecoins be a thing in our future finance systems?
– In case of covid-19 AI has failed us. (rcmd by reader)
https://www.quantamagazine.org/animals-can-count-and-use-zero-how-far-does-their-number-sense-go-20210809/ – Even animals can count and use zero. A complex and interesting article, like all of them on Quanta.
https://xamat.medium.com/on-the-usefulness-of-the-netflix-prize-403d360aaf2 – How is the Netflix Prize useful and mainly what it is? (rcmd by reader)
https://www.analyticsvidhya.com/blog/2021/08/a-hands-on-guide-to-build-your-first-convolutional-neural-network-model/ – Try to train your own CNN model.
https://ericmjl.github.io/essays-on-data-science/machine-learning/graph-nets/ – Graph deep learning in an easy to understand article.
https://github.com/dair-ai/ML-YouTube-Courses#-ml-youtube-courses – List of ML courses on YouTube. You probably know most of them. But still an interesting list.
Data & Libraries
https://medium.com/airbnb-engineering/how-airbnb-built-wall-to-prevent-data-bugs-ad1b081d6e8f – Data quality is important, maybe even more than models. How Airbnb has created a data wall that protects their high quality standards.
https://github.com/sfu-db/connector-x – ConnectorX is supposedly the fastest and most memory efficient way to load data from a database into Python.
Video & Podcast
https://www.youtube.com/channel/UCVhQ2NnY5Rskt6UjCUkJ_DA – YouTube channel ArjanCodes will make you a better Python developer. (rcmd by reader)
https://open.spotify.com/episode/6MqXf9p7CWkvLRYQcghawq – Head of data tribe z České spořitelny Martin Gerneš byl hostem Datacastu. (rcmd by reader)
https://www.youtube.com/watch?v=lr1uK24SND8 – Amazing video from 1953 how to set up a navy mechanical fire control computer. And there is a manual. This is like time traveling and you’re gonna see marvelous things.
Papers & Books
https://www.statlearning.com/ – 2nd EDITION of Introduction to statistical learning! And complementary code built in tidymodels. (rcmd by reader)
https://arxiv.org/abs/2010.00554 – PCA as a Nash equilibrium with eigenvectors as players maximizing their utility functions. (rcmd by reader)
https://www.bis.org/fsi/publ/insights35.htm – This paper will show us how AI might be regulated in the financial sector by authorities.
Behind the Fence
https://www.pythonjobshq.com/jobs/75900332-data-engineer-python-postgresql-at-research-affiliates – Data Engineer in
Research Affiliates, Newport Beach, USA.
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