docker-data-science-at-the-command-line contains everything to build a doker container to use with the book Data Science at the Command Line.

To build the container :

cd docker-data-science-at-the-command-line
docker build -t docker-data-science-at-the-command-line .

To run the container :

docker run -v `pwd`:/data -it docker-data-science-at-the-command-line /bin/bash

Hadoop Web UIs and logs

A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting ...

scikit-learn comes with a few standard datasets, for instance the iris and digits datasets for classification. The iris dataset consists of measurements of three different species of irises ...

Plotting the earthquakes of the last 30 months with R and the the National Earthquake Hazards Reduction Program (NEHRP) feed ...

A confusion matrix, also known as a contingency table or an error matrix or tavle of confusion, is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one (in unsupervised learning it is usually called a matching matrix).

It is a table …

This post follows the R : Exploring Data for Machine Learning Modeling post, exploring linear model in the context of machine learning.

We'll still use the Wage dataset from the ISLR package.
This dataset reports wage and other data (age, education, jobclass, etc.) for a group of 3000 male workers in …

These are my notes on the Practical Machine Learning course (Week2: Plotting Predictors - Tutorial).

When exploring data for Machine Learning, we're looking for:

• imbalance outcomes/predictors
• outliners
• groups of outcome points not explained by any of the predictors
• skewed variables (that needs to be transformed)

We'll use the Wage dataset …

The Central Limit Theorem states that the distribution of sample statistics (e.g. mean) is approximatively normal, regardless of the underlying distribution, with mean = \(\mu\) and variance = \(\sigma^2\) ...