Share0 Tweet0 Share0 Machine learning & Data Science courseAre you interested in learning machine learning & data science? If yes, click on the button to enroll today with 90% discount. Buy It Now! Hi guys are you working on neural networks or deep learning models and came across activation functions? And wondering what activation function […]

## What is Activation Function & Why you need it in Neural Networks

## Evaluation Metrics for Regression models- MAE Vs MSE Vs RMSE vs RMSLE

Share0 Share +10 Tweet0 Machine learning & Data Science course Everything you need to start your career as data scientist. Learn machine learning fundamentals, applied statistics, R programming, data visualization with ggplot2, seaborn, matplotlib and build machine learning models with R, pandas, numpy & scikit-learn using rstudio & jupyter notebook.More than 15 projects, Code files […]

## What is Deep Learning?

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## How to become a Data Scientist or Machine Learning engineer?

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## How to do KNN with Python & Sci-Kit Learn

KNN or K-nearest neighbor is one of the easiest and most popular machine learning algorithm available to data scientists and machine learning enthusiasts. In this post, we are going to implement KNN model with python and sci-kit learn library. You can also implement KNN in R but that is beyond the scope for this post. […]

## How To Use Azure ML Studio to perform Multiclass Logistic Regression

Azure ML studio has become of the most popular machine learning tool among machine learning community and it is currently widely used across industries & geographies. Thanks to azure’s hold in enterprise software development, it wasn’t a big surprise. Azure ML studio makes it easier to run all kind of machine learning models using built-in […]

## R Programming Tutorial-R Operators

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## How to Perform ANOVA analysis in R for Marketing

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## Business Analytic Part 9-Regression Analysis

Welcome to the chapter 9 of business analytics tutorial where we will start with subjects related to predictive modelling in data science. In this chapter, we will cover Regression analysis and its variants. We will first go through the definitions and concepts and later cover them in detail with case studies to see their real […]

## Business Analytics Part 8-More Data Science & Statistical Concepts

We have already covered many data science and statistical concepts in previous chapters. We will continue with basic and advance data science related statistical concepts with their business applications in this chapter as well. Data Science & Statistical Concepts Skewness Skewness is the measure of the asymmetry or deviation from the symmetry in statistical analysis. […]

## Business Analytics Part 7- Descriptive Analysis Vs Inferential Analysis

You have already covered good ground if you have been following this tutorial from beginning but if you haven’t, you can simply use the link for previous chapters at the bottom of each post. So far, we have covered various statistical tests like f test, p test, one way ANOVA, two ANOVA etc. They are […]

## Business Analytics Part 6- Two Way Analysis of variance (ANOVA)

In the last chapter about one way ANOVA, we studied how one way ANOVA is used to measure a variable or output or factor for more than two groups at different interval or level. Suppose we instead of one variable, we have two variables. In that case, we will two way ANOVA. Welcome to part […]

## Business Analytics Part 5- One Way Analysis of Variance (ANOVA)

As we have already seen been through t test and f test in previous chapters, it is a good time to look at ANOVA in detail. In this chapter we will go through One Way ANOVA. In the last chapter, we have mentioned that t test for independent variable is equivalent to ANOVA if you […]