# Batch Normalization and why it works

Batch Normalization (BatchNorm) is a very frequently used technique in Deep Learning, however, the reason why it works is often interpreted ambiguously. Continue reading Batch Normalization and why it works

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# Tag: Gradient Descent

# Batch Normalization and why it works

# Logistic Regression: Advantages and Disadvantages

# Logistic Regression tutorial

# Linear Regression in Python

# How to make a Linear Regressor? (theory)

# Advantages of Linear Regression

Batch Normalization (BatchNorm) is a very frequently used technique in Deep Learning, however, the reason why it works is often interpreted ambiguously. Continue reading Batch Normalization and why it works

In the previous blogs, we have discussed Logistic Regression and its assumptions. Today, the main topic is the theoretical and empirical goods and bads of this model. Continue reading Logistic Regression: Advantages and Disadvantages

Following the previous overview, this article attempts to delve deeper into Logistic Regression. Continue reading Logistic Regression tutorial

Train and cross-validate your Linear regression on Python with pre-defined or customized evaluation functions. Continue reading Linear Regression in Python

This article presents the formulas for coming up with the best-fitted linear regression line. Continue reading How to make a Linear Regressor? (theory)

Linear regression is frequently used in practice because of these 7 reasons. Continue reading Advantages of Linear Regression