We always aim to reduce the generalization error of a classification model. Generalization error gives the idea that how well the model do on unseen data. But even after getting the lowest generalization error or highest accuracy, how confident are we that it shall hold on new/unseen data? A confidence…

This article show the features helping student learn and visualize data and model results in Orange using Breast Cancer dataset.

Dataset used here is taken from UCI Machine Learning repository, attributes are categorical and predicts weather the patient shall have recurrence or cancer or not.

For Starters, its easy to see the distribution of each column using distributions under visualization.

Easy to see scatter plot-

Decision Boundary-

Clustering, t-SNE and DBSCAN.

Complete quick and dirty workflow is as follows-

Explores a orderbook sample using Dtale and Autoviz.

So, I recently got an email from Kaggle that there is a new challenge uploaded from Optiver for Volatility prediction. Let’s try to use auto EDA tools to explore a stock.

Using Dtale-

There is describe option which shows the details of each column-

Histogram-

Quick Dashboard using Tableau

Data Source — http://data.uis.unesco.org/

A simple time-lapse on map-

A simple Rank chart of top 5 countries-

This Story simply explores the dataset taken from data.world using Tableau.

A Line graphs for analyzing number of arrest each crime time from 2001 to 2012.

I came across a dataset consisting slogans of various company's on kaggle. Rather than watching a movie I thought to distract myself with this dataset. I tried running sentiment analysis of slogans to find something interesting.

As a ritual after performing some data quality checks, I found out that a…

This article explain various window models for keeping relevant data from continuous stream of data.

Let’s assume we have a stream of tweets coming for a particular hashtag. Initially there were 2 clusters based on emotions, positive and negative we could map the tweets to. However, as the tweets are…

This article is a little demonstration of Bisecting K-means. We all are familiar with K-means, let’s see what Bisecting the data does.

So, the infamous problem of centroid initialization in K-means has many solutions, one of them is bisecting the data points. As the main goal of the K-means algorithm…