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Course Overview

1.Intro to Deep Learning

1.1.Linear Regression
1.2.Assignment - Polynomial Regression
1.3.Logistic Regression
1.4.Assignment - Multiclass Classification
1.5.Multi Layer Perceptron - Motivation

2.Deep Neural Networks

2.1.Neural Network Architectures
2.2.Batch Training
2.3.Optimizers
2.4.Learning Rate
2.5.Bias & Variance
2.6.Overfitting & Regularization
2.7.ANN - Medical Diagnosis
2.8.ANN - Computer Vision
2.9.ANN - Natural Language Processing

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Last updated on Sep 6, 2019

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