![]() ![]() Machine learning, artificial intelligence, cognitive computing, deep learning. the linear algebra behind each algorithm or optimization operations! The best way is to find a data, a working example script and fiddle with them. Video editing using BlenderĮach statement is commented so that you easily connect with the code and the function of each module - remember one does not need to understand everything at the foundational level - e.g. GhostView to convert PDF into other formats such as PNG -Compress, merge, scale, rotate and delete pages from PDF files using PyPDF2.Video Editing - Image Filtering, Masking and Denoising - Image Deskewing - Video Editing using FFmpeg - Animations like PowerPoint - Morphological Operations - Connected Component Labeling - Find and Draw Contours in an Image.Digit Recognition and ANN MLP classifications - Computer Vision.Decision Tree / Random Forest Classification with Python + sciKit-Learn. ![]() SVM using Python + sciKit-Learn - Naive Bayes classification - Anomaly Detection - Recommender Systems and Collaborative Filtering.K-Nearest Neighbours (KNN) using Python + sciKit-Learn - clustering by K-means (GNU OCTAVE) - Probability in Machine Learning.Linear Algebra - Principal Component Analysis - PCA (GNU OCTAVE).Python - Python Argument Parsing - Vectorization - Slicing of Arrays - OOP in Python - Web Scraping in Python Regression and Logistic Regression (GNU OCTAVE).On this page, you will find working examples of most of the machine learning methods in use now-a-days! Human Brain: Have you tried to search online the keywords "number of neurons in the brain"? The answer is invariably 100 billions! There is another data that we use only 1% of brain and hence do the number 1 billion neurons not astonish you? Can we build a machine and the learning algorithm to deal with similar number of neurons? ![]()
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