Data Science
Notes
Data science is the field that focuses on extracting insights and causal links from data. It uses statistical research methods in order to verify that the results are credible. Usually, data science is performed using Artificial Intelligence, meaning that it's the "computers job" to detect those links, and our job to verify that those results hold true.
Dangers of DS
Some common problems that can occur while validating results of ML models:
- Overfitting - The model has fitted itself too much to the training data, and will preform worse when it is deployed with new data
- Missing data (article) - The input data will likely include missing values, and we have to determine how to deal with them before inserting the data to the model
- Data Drift (article) - Data changes over time, for example the avg age in the population changes, and patterns change. We need to keep track of those variables and perhaps redesign the model accordingly.
General Topics
Useful Packages
general - pytorch, tenserflow. NLP - spacy web scrapping - scrapy, beautiful soup Famous models - Bert (nlp), GPT-3 (NLP)
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Courses
Statistics for Data Science (course) Python for data science (course) Machine Learning A-Z (course) The data science bootcamp (course)
Creators
Thu Vu data analytics towards data science Practical AI podcast
Websites
Photos
https://unsplash.com https://www.pexels.com https://pixabay.com
Colors
https://coolors.co https://colorhunt.co https://rgbcolorcode.com
Icons
https://www.flaticon.com https://jrgraphix.net/r/Unicode/25A0-25FF https://covercons.vercel.app https://lucide.dev https://www.webfx.com/tools/emoji-cheat-sheet/
Misc Tools
https://www.stackbit.com https://lottiefiles.com https://www.postman.com https://share.streamlit.io https://try.jsoup.org https://huggingface.co https://regex101.com
AI Tools
https://www.promeai.pro/ https://www.bluewillow.ai https://chat.openai.com https://playgroundai.com https://openai.com/dall-e-3 https://huggingface.co/spaces/AP123/IllusionDiffusion https://www.perplexity.ai