66daysofdata

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+. Just updated 2025H1 - GenAI*

"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)"

Discord Youtube

GenAI

• Applied LLM Intro

• GenAI Intro

• Resources

• Sample Whatsapp Assistant built on AWS

Curated Recent Reads

• LLMs in Production: A Comparison of GCP, Azure, and AWS by Rafal Lagowski

• Guided Code Generation with LLMs: A Multi-Agent Framework for Complex Code Tasks by Amr Almorsi, et al

• List of LLM Evaluation Papers

• Chain-of-Verification Reduces Hallucination in Large Language Models by Shehzaad Dhuliawala ,et al

• FACTIFY: A Multi-Modal Fact Verification Dataset by Ashwarya Reganti, et al

• LLM Engineering Resources by Ed Donner along with a 8 week hands-on course

• Gallery of interesting Jupyter Notebooks by Lorena Barba

• From Python to Numpy by Inria researcher Nicolas P. Rougier

• Vectorize your Conditional Loops in Python by Tirthajyokti Sarkar, regularly used by Data Scientists to speed up data transformations in code

• Combinatorial Optimization in Python by Google Developers

• Uber Engineering Combats Fraud, Builds 'Mastermind', using Python's Abstract Syntax Tree by Yifu Dao and Isabel Geracioti

• Improving Machine Learning Model Performance by Andrew Ng

• The Hundred-Page Machine Learning Book by Andriy Burkov

• Data Scientist Toolkit by Andriy Burkov

• Deep Learning Recommender, Survey and Perspectives, by Zhang, Yao, et al

• Develop a NLP Model in Python & Deploy It with Flask, by Susan Li

• Kubeflow at LinkedIn by Abin Shahab & Tengfei Mu, LinkedIn. Kubeflow is an open source Kubernetes-native platform for orchestrating and deploying machine learning workloads

• Is Docker Swarm dead (vs Kubernetes)?

• Quantitative Economics using Python, Stachurski, John

• NYU Deep Learning SP20, speakers Yann Le Cun, Alfredo Canziani

• Schema Unification with Snowflake, Chinmayee Lakkad

• Using DBT to Execute ELT pipelines in Snowflake

• Redox Connector to Azure for Healthcare, John Aven

• Redox Git and its HL7v2 parser/generator

• Endava Demo, healthcare context HL7FHIR

• Spark NLP to categorize publications, healthcare context

• 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

• Data Engineer Newsletter by Zach Wilson with even more DE resources

• Non-native vs Native Graph Technology by Neo4J

• System Design Primer by Donne Martin

Resources

• Awesome Data Engineering TIL

Data Sets

• /r/datasets - A subreddit for sharing datasets

• Institute for Reproducible Research

• Travel related Amadeus and other travel APIs via Altexsoft

Excel

Microsoft Excel is still widely used today for starting analyses e.g. in healthcare, government, non-profit. Sampling of useful resources.

• Analysis Toolpak

• Via David Langer, free and paid training on Excel for Business, R and even courses on Regression and Machine Learning and youtube channel

• Via Chandoo, he used to have a lot of free stuff but now he also does paid training

• Non-online resource I recommend is Gerald Knight's O'Reilly book "Analyzing Business Data with Excel"

Support Me

If you like this list consider supporting me!

Credit

Nod to respective authors above for their respective works as indicated above.

License