class 01
: Introduction to ML and Basics of Python programming.class 02
: Basics of Stats and Numerical computationclass 03
: K-nearest neighboursclass 04
: Face recognition with KNNclass 05
: K-means clusteringclass 06
: Decision Tress and Dominant Color Extraction Projectclass 07
: Principal Component Analysisclass 08
: Linear Regressionclass 09
: Logistic Regressionclass 10
: Neural Networks with Numpyclass 11
: Neural Nets with PyTrochclass 12
: Convolutional Neural Networksclass 13
: AutoEncoders and Dropout in NNclass 14
: Markov Chainsclass 15
: Attention Mechanisms and RNNclass 16
: Word2Vec algorithms and LSTMclass 17
: Applications of LSTMsclass 18
: Scraping and Genetic Algorithmsclass 19
: Deep Dream and Neural Artclass 20
: RCNNclass 21
: RLclass 22
: Naive Bayes and SVM
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Noida Batch for Perceptron (Machine Learning) Summer 2018
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