Algorithms to be used : SVM Random Forest Naive Bayes Decision Trees Logistic Regression Ensemble Methods The number of features chosen (say k) => k << N2 Continue reading E2E Deep Learning – example

Supervised Learning : Requires labeled data to train. Unsupervised Learning : Cluster and make patterns out of unlabeled data. Semi-supervised Learning : Combination of both Continue reading M.L. types

  Artificial Intelligence : Sence, act, adapt and reason. Machine Learning : Algorithms whose performance improves over time when exposed to datasets. Deep Learning : Subset of M.L. in which multi-layered neural network learns from various amounts of data. Continue reading AI vs ML vs Deep Learning