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PCA or principal component analysis is a dimensionality reduction technique that can help us reduce dimensions of dataset that we use in machine learning for training. It helps with famous dimensionality curse problem. In this video we will understand what PCA is all about, write python code for handwritten digits dataset classification and then use PCA to train the same model using PCA. Code: https://github.com/codebasics/py/blob/master/ML/18_PCA/PCA_tutorial_digits.ipynb Exercise: https://github.com/codebasics/py/blob/master/ML/18_PCA/pca_exercise.md ⭐️ Timestamps ⭐️ 00:00 Theory 10:00 Coding 28:07 Exercise 🎥 Codebasics English Channel: https://www.youtube.com/c/codebasics #️⃣ Social Media #️⃣ 🔗 Discord: https://discord.gg/r42Kbuk 📸 Instagram: https://www.instagram.com/codebasicshub/ 🌎 Website: https://www.skillbasics.com/ 🔊 Facebook: https://www.facebook.com/codebasicshub 📱 Twitter: https://twitter.com/codebasicshub 📝 Linkedin (Personal): https://www.linkedin.com/in/dhavalsays/ 📝 Linkedin (Codebasics): https://www.linkedin.com/company/codebasics/ ❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.
