Unsupervised Feature Selection for Machine Learning in 5 Mins скачать в хорошем качестве

Unsupervised Feature Selection for Machine Learning in 5 Mins

In this video, we dive into unsupervised feature selection techniques, which are essential for reducing the number of features used in machine learning models. Learn about powerful algorithms like PCA, ICA, NMF, TSNE, and autoencoders that help discover important patterns and similarities in data without explicit instructions. Stay tuned for a concise overview of these techniques in under five minutes! Don't miss the videos on 📌 Filtered-Based Feature Selection for Machine Learning In 5 Mins:    • Filtered Based Feature Selection for Machi...   📌 Feature Selection for Machine Learning In 5 Mins:    • Feature Selection for Machine Learning In ...   Here's the full article for both supervised and unsupervised feature selection techniques, including filter-based, wrapper-based, and embedded approaches: https://www.stratascratch.com/blog/fe... ______________________________________________________________________ 👉 Subscribe to my channel: https://bit.ly/2GsFxmA 👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81 👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ 👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsY... 👉 Practice more real data science interview questions: https://platform.stratascratch.com/co... ______________________________________________________________________ Timeline: Intro: (0:00​​​) What is unsupervised Feature selection: (0:42) Principal Component Analysis: (1:27) Independent Component Analysis: (2:22) Non-Negative Matrix Factorization: (2:58) t-distributed Stochastic Neighbor Embedding: (3:49) Autoencoder: (4:21) Conclusion: (4:59) ______________________________________________________________________ About The Platform: StrataScratch (https://platform.stratascratch.com/co...) is a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases. So, if you want more interview practice with real data science interview questions, visit https://platform.stratascratch.com/co.... All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from the StrataScratch team, you can use ss15 for a 15% discount on the premium plans. ______________________________________________________________________ Contact: If you have any questions, comments, or feedback, please leave them here! Feel free to also email us at team@stratascratch.com ______________________________________________________________________ #featureselection #machinelearning #datascience #machinelearningalgorithm #machinelearningwithpython #datascienceskills #python #unsupervisedlearning #supervisedlearning