Hi,
hopefully it’s Friday and hopefully you’re reading the bulletin! For me the most interesting is a Python library SDV from Data & Libraries that generates fake data. Very useful is also a article about proper „giting“ in Computer Science & Science.
As always, enjoy your reading.
Analytical
https://ai.stanford.edu/blog/learning-from-language/ – Use NLP to build not only text classifiers with language explanations.
https://opendatascience.com/retraining-machine-learning-models-in-the-wake-of-covid-19/ – Covid is affecting everything, therefore even ML models, so maybe it’s time to retrain them.
https://medium.com/anomalo-hq/dynamic-data-testing-f831435dba90 – We are used to test software, monitor our models, but we should also continuously test our data.
Computer Science & Science
https://daniel.haxx.se/blog/2020/11/09/this-is-how-i-git/ – How to git properly? Daniel Stenberg, lead dev of curl, gives you some hints. (rcmd by reader)
https://medium.com/better-programming/modern-day-architecture-design-patterns-for-software-professionals-9056ee1ed977 – Design patterns for software architecture of modern applications – how to meet scalability, availability, security, reliability, and resiliency demands. (rcmd by reader)
https://stackoverflow.blog/2020/11/23/the-macro-problem-with-microservices/ – The dark side of microservices, which problems they brought and how to solve them. (rcmd by reader)
Graphs and Visualizations
https://www.analyticsvidhya.com/blog/2020/11/classification-model-simulator-application-using-dash-in-python/ – Use Dash for creating classification models with an app.
Business and Career
https://github.com/datastacktv/data-engineer-roadmap – Roadmap for data engineer. At least it shows you which technical stack is in demand.
https://www.kdnuggets.com/2020/11/moving-data-science-machine-learning-engineering.html – In data science, there is new discipline, machine learning engineering that gives answer on question: What can we build with machine learning models developed by data scientist, and how? (rcmd by reader)
https://www.theguardian.com/technology/2020/nov/24/bitcoin-price-high-19000-cryptocurrency-covid – Bitcoin is surging (again) and investors are optimistic about it.
Pop
https://towardsdatascience.com/create-your-own-smart-baby-monitor-with-a-raspberrypi-and-tensorflow-5b25713410ca – Finally, a reason to have a baby! You can create your own baby monitor. (rcmd by reader)
https://undark.org/2020/11/18/best-strategy-to-deploy-covid-19-vaccine/ – Covid-19 vaccines are incoming and there should be a strategy for their optimal rollout.
https://venturebeat.com/2020/11/19/facebooks-improved-ai-isnt-preventing-harmful-content-from-spreading/ – Does Facebook’s AI stop hate speech and misinformations? And here you can read how the moderation works.
Education
https://thegradient.pub/interpretability-in-ml-a-broad-overview/ – What current research tells us about interpretability of ML and what is the future?
https://opendatascience.com/understanding-the-temporal-difference-learning-and-its-predication/ – Learn about Temporal Difference Learning.
https://www.technologyreview.com/2020/10/30/1011435/ai-fourier-neural-network-cracks-navier-stokes-and-partial-differential-equations/ – AI is solving partial differential equation and it is 1,000 times faster than traditional mathematical formulas. (rcmd by reader)
Data & Libraries
https://towardsdatascience.com/synthetic-data-vault-sdv-a-python-library-for-dataset-modeling-b48c406e7398 – SDV (Synthetic Data Vault) will help you to generate fake data based on the actual data.
https://github.com/AI4Finance-LLC/FinRL-Library – FinRL is a library that helps you to develop your own stock trading strategy with help of deep reinforcement learning.
https://docs.seldon.io/projects/alibi-detect/en/latest/index.html – Alibi Detect is a Python library that detects outliers, adversarials and drifts.
Papers & Books
https://www.topbots.com/ai-machine-learning-research-papers-2020/ – Summarized Top 10 ML papers in 2020. (rcmd by reader)
https://arxiv.org/pdf/2010.14501v2.pdf – Memory optimization for deep networks.
https://arxiv.org/pdf/2010.15703v1.pdf – Large neural networks compressing.
Behind the Fence
https://www.jobsatosu.com/postings/104217 – Data Scientist in The Ohio State University, Columbus, USA.
Joke
https://i.redd.it/4b18ug1wef161.jpg – Every single time…
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