# Gradient Descent – Gradients Brew

Gradient Descent is the backbone of any neural network. In this post, we will explore Gradient descent and some of its variants.

Tutorials for Data Science , Machine Learning, AI & Big Data

Tutorials for Data Science , Machine Learning, AI & Big Data – Analytics

Gradient Descent is the backbone of any neural network. In this post, we will explore Gradient descent and some of its variants.

In this tutorial we will talk in brief about a class of Machine learning problems – Classification Problems. We will try to establish the concept of classification and why they are so important. Continue reading “Introduction to Classification Problems in Machine Learning”

This tutorial is a set of 15 hour videos by acclaimed experts in the area of machine learning and statistics from Stanford. It is suitable for Beginners as well as experts Continue reading “Tutorial : Beginner to advanced machine learning in 15 hour Videos”

In this tutorial we will learn how to interpret another very important measure called F-Statistic which is thrown out to us in the summary of regression model by R.

Continue reading “R Tutorial : How to interpret F Statistic in Regression Models”

This tutorial talks about interpretation of the most fundamental measure reported for models which is R Squared and Adjusted R Squared. We will try to give a clear guidelines for interpreting R Squared and Adjusted R Squared

Continue reading “R Tutorial : Interpretation of R Squared and Adjusted R Squared in Regression”

In this tutorial we will discuss about effectively using diagnostic plots for regression models using R and how can we correct the model by looking at the diagnostic plots.

Continue reading “R Tutorial : How to use Diagnostic Plots for Regression Models”

In this tutorial we will learn a very important aspect of analyzing regression i.e. Residual Analysis. Residual Analysis is a very important tool used by Data Science experts , knowing which will turn you into an amateur to a pro.

Continue reading “R Tutorial : Residual Analysis for Regression”

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