Large Scale Learning With the increase in size of training data, it becomes important to optimize algorithm and parallelize processes to minimize the training time and manage resource utilization. machine-learning andrew-ng
Recommender Systems A recommender system or a recommendation system is a subclass of information filtering system that seeks to predict the "rating" or "preference" a user would give to an item. machine-learning andrew-ng
Anomaly Detection In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset. machine-learning andrew-ng
Principal Component Analysis A mathematical procedure that transforms a number of (possibly) correlated variables into a (possibly smaller) number of uncorrelated variables called principal components. machine-learning andrew-ng
K-Means Clustering K-means clustering, a method from vector quantization, aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. machine-learning andrew-ng
Support Vector Machine A SVM is a discriminative classifier formally defined by a separating hyperplane. Given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. machine-learning andrew-ng
Error Metrics for Skewed Classes and Using Large Datasets The error metrics like mean-squared error do not work for highly imbalanced class. Also, why is it that using larger dataset is always advised? machine-learning andrew-ng
Evaluation of Learning Algorithm Often it is hard to decide what is right and what is not in evaluating the effectiveness of an algorithm. Which step would should one try and evaluate among the heap of probable options that can help. machine-learning andrew-ng
How to train your Neural Network? Basic set of steps to follow while training a neural network. A lot of these are just recommendations. There are no rules in the world of neural networks. machine-learning andrew-ng