In support of the #66daysofdata initiative and the data science community, this repo is a TIL collection of data engineering and data science code and experiments for 66 days+.
"Why 66 days? Because it is the average amount of days needed to establish a new habit. Creating solid data science habits is one of the most powerful things we can do to have longevity in this every dynamic field of technology. (Ken Jee)"
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Vectorize your Conditional Loops in Python by Tirthajyokti Sarkar
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Deep Learning Recommender, Survey and Perspectives, by Zhang, Yao, et al
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Develop a NLP Model in Python & Deploy It with Flask, by Susan Li
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NYU Deep Learning SP20, speakers Yann Le Cun, Alfredo Canziani
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Redox Git and its HL7v2 parser/generator
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Fireside Chat with Aparna Ramani & Yann LeCun at May 2022 Data@Scale, touches on self-supervised machine learning and emerging DS trends along with Ms. Ramani's keynote
Microsoft Excel is still widely used today for starting analyses e.g. in healthcare, government, non-profit. Sampling of useful resources.
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Via David Langer, free and paid training on Excel for Business, R and even courses on Regression and Machine Learning and youtube channel
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Via Chandoo, he used to have a lot of free stuff but now he also does paid training
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