PCA To Reduce Features to 2 Dimensions

hi, i'm expert in python and machine learning, I've implemented a lot of ML algorithms from scratch using python, feel free to check my work [login to view URL], is this part of other project or you need to write the algorithm it self to reduce data dimensions ?

Hello, I know all basics of PCA, eigen values and eigen vectors. I have successfully completed 45 Machine Learning/ AI projects in last 6 months with 5 ratings. Your project attracted my attention at first glance, because I've really rich experience in Machine Learning with R (R studio) and Python Programming. I am having 5+ years of experience in Data Science using tools like Python, R, Spark. I have worked on several similar projects before! I'm really confident about your project, and very eager to join your project. If we have a chance to cooperate, I'll do my best to provide wonderful result. Some of the Projects I have worked upon - 1) Twitter Troll Classification using _Python_ 2) Story point prediction analyzing research pdf papers _ Regression model NLP 3) Face recognition using OpenCV / Python 4) Feature selection using BORUTA and prediction in _R_ 5) Employee Churn prediction Model using _Python_(2 Projects) 6) R programming real time assignment _R_ 7) Twitter Sentiment Analysis using Python _R_ You can check my all projects and detailed portfolio on my profile || Link

Hi, I am interested in doing it. we can discuss more about it in chat. i would like to know size of your data set and how many dimensions it has initially and which library to use for principal component analysis . i will be available in chat . if you are interested you can contact me there. Thanks