Machine Learning Tutorial Python | Machine Learning For Beginners - Data Science & Machine Learning Project - Part 4 Feature Engineering | Image Classification

In this video, we will use cropped images and apply wavelet transform to extract meaning features that can help with image identification. You need to understand many important concepts such as time vs frequency domain, fourier transform, representing images as frequency etc. You will find below resources to understand these concepts. USing wavelet transform and a raw pixel image we will create our X and use class labels as y. These X and y will be used for model training. Feature engineering techniques in this tutorial will enhance your understanding on how they can be used to create powerful prediction function. Code: https://github.com/codebasics/py/blob/master/DataScience/CelebrityFaceRecognition/model/sports_celebrity_classification.ipynb Resources to understand signal processing concepts: My friend Iman's youtube channel: https://www.youtube.com/channel/UCVkatNMgkEdpWLhH0kBqqLw Representing image as a frequency: https://www.youtube.com/watch?v=xrTor1uw5iI Fourier transform: https://www.youtube.com/watch?v=spUNpyF58BY&t=423s Special thanks to, Debjyoti Paul (Amazon Data Scientist): For help with entire project Do you want to learn technology from me? Check https://codebasics.io/ for my affordable video courses. Website: http://codebasics.io/ Facebook: https://www.facebook.com/codebasicshub Twitter: https://twitter.com/codebasicshub