The Ultimate Guide to 12 Dimension Reduction Techniques (20 pages) Python - Pulkit Sharma Popular Posts: The Ultimate guide to AI, Data Science & Machine Learning, Articles, Cheatsheets and Tutorials ALL in one place https://lnkd.in/eiPz3GJ SELF-Supervised Learning (122 pages) https://lnkd.in/fHh9u3a DATA FALLACIES TO AVOID https://lnkd.in/eDUpGgN A Practical Introduction to Prescriptive Analytics (with Case Study in R) https://lnkd.in/ecevsJe Advantages Drawbacks Applications of TOP 10 algorithms (23 pages) https://lnkd.in/eXMHFeK Feature Engineering - Getting most out of data for predictive models (76 slides) https://lnkd.in/d82CKCh Extracting Features from Text - A Step-by-Step NLP Guide https://lnkd.in/evD9-Nh Which machine learning algorithm to use? https://lnkd.in/e5XMjrQ Visual Explanation of Deep Learning (21 pages) https://lnkd.in/eiiCB9w Step by Step Guide to Data Cleaning with Python(NumPy and Pandas) (15 pages) https://lnkd.in/eGdexzq The Ultimate Guide To Speech Recognition With Python (23 pages) https://lnkd.in/ehdwVzg Guided model building mindmap https://lnkd.in/fTNKAxp #machinelearning #artificialintelligence #datascience #ml #ai #deeplearning # #tutorial #learn #python #R #dimensionreduction To follow posts: https://lnkd.in/ev9S2hh
So many of the techniques are missing gram schmidt LdA SvD CCA LsI L1 and L2 regu in the feature space SvM in the observation space And the list goes on.....
good information
Great links
ML/NLP/LLM /Agents Google Developer Expert for Machine Learning / Mentor at OpenClassrooms / Instructor at Coursera/ Co-founder of GalsenAI
5 年thanks. it is worth mentioning that Low variance filter should be applied after normalizing the data with something like MinMax scaler. Also eliminate outliers.