The Data Science Process - A Visual Guide (Part 1)

In this Part 1 video, I will be covering the data science process which provides a systematic approach for tackling a data problem. By following through on these recommended guidelines, you will be able to make use of a tried-and-true workflow in approaching data science projects. Particularly, I'll be going over the standard procedures for carrying out Data Science projects. I'll be covering the Data Science Life Cycle, CRISP-DM and OSEMN frameworks. This video is based on the Medium article that I published in Towards Data Science "The Data Science Process - A Visual Guide to Standard Procedures in Data Science" ✅ https://towardsdatascience.com/the-data-science-process-a19eb7ebc41b 🌟 Buy me a coffee: https://www.buymeacoffee.com/dataprofessor 🌟 Download Kite for FREE (AI-powered coding assistant that will help you code faster and smarter) https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=dataprofessor&utm_content=description-only 👇 Subscribe: If you're new here, it would mean the world to me if you would consider subscribing to this channel. ✅ Subscribe: https://www.youtube.com/dataprofessor?sub_confirmation=1 ⭕ Playlist: Check out our other videos in the following playlists. ✅ Data Science 101: https://bit.ly/dataprofessor-ds101 ✅ Data Science YouTuber Podcast: https://bit.ly/datascience-youtuber-podcast ✅ Data Science Virtual Internship: https://bit.ly/dataprofessor-internship ✅ Bioinformatics: http://bit.ly/dataprofessor-bioinformatics ✅ Data Science Toolbox: https://bit.ly/dataprofessor-datasciencetoolbox ✅ Streamlit (Web App in Python): https://bit.ly/dataprofessor-streamlit ✅ Shiny (Web App in R): https://bit.ly/dataprofessor-shiny ✅ Google Colab Tips and Tricks: https://bit.ly/dataprofessor-google-colab ✅ Pandas Tips and Tricks: https://bit.ly/dataprofessor-pandas ✅ Python Data Science Project: https://bit.ly/dataprofessor-python-ds ✅ R Data Science Project: https://bit.ly/dataprofessor-r-ds ✅ Weka (No Code Machine Learning): http://bit.ly/dp-weka ⭕ Recommended Books: 🌟https://kit.co/dataprofessor ✅ Hands-On Machine Learning with Scikit-Learn : https://amzn.to/3hTKuTt ✅ Data Science from Scratch : https://amzn.to/3fO0JiZ ✅ Python Data Science Handbook : https://amzn.to/37Tvf8n ✅ R for Data Science : https://amzn.to/2YCPcgW ✅ Artificial Intelligence: The Insights You Need from Harvard Business Review: https://amzn.to/33jTdcv ✅ AI Superpowers: China, Silicon Valley, and the New World Order: https://amzn.to/3nghGrd ⭕ Stock photos, graphics and videos used on this channel: ✅ https://1.envato.market/c/2346717/628379/4662 ⭕ Follow us: ✅ Medium: http://bit.ly/chanin-medium ✅ FaceBook: http://facebook.com/dataprofessor/ ✅ Website: http://dataprofessor.org/ (Under construction) ✅ Twitter: https://twitter.com/thedataprof/ ✅ Instagram: https://www.instagram.com/data.professor/ ✅ LinkedIn: https://www.linkedin.com/in/chanin-nantasenamat/ ✅ GitHub 1: https://github.com/dataprofessor/ ✅ GitHub 2: https://github.com/chaninlab/ ⭕ Disclaimer: Recommended books and tools are affiliate links that gives me a portion of sales at no cost to you, which will contribute to the improvement of this channel's contents. #datascienceprocess #crispdm #osemn #machinelearning #lecture #bigdata #QSAR #QSPR #machinelearning #datascienceproject #randomforest #decisiontree #svm #neuralnet #neuralnetwork #supportvectormachine #python #learnpython #pythonprogramming #datascience #datamining #bigdata #datascienceworkshop #dataminingworkshop #dataminingtutorial #datasciencetutorial #ai #artificialintelligence #tutorial #dataanalytics #dataanalysis #machinelearningmodel #dataprofessor