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Articles in this category

The problem of overfitting in machine learning algorithms

Overfitting makes linear regression and logistic regression perform poorly. A technique called "regularization" aims to fix the problem for good. written on September 02, 2018

The cost function in logistic regression

Preparing the logistic regression algorithm for the actual implementation. written on October 29, 2017

Introduction to classification and logistic regression

Get your feet wet with another fundamental machine learning algorithm for binary classification. written on July 17, 2017

How to optimize the gradient descent algorithm

A collection of practical tips and tricks to improve the gradient descent process and make it easier to understand. written on April 01, 2017

Multivariate linear regression

How to upgrade a linear regression algorithm from one to many input variables. written on March 05, 2017

The gradient descent in action

It's time to put together the gradient descent with the cost function, in order to churn out the final algorithm for linear regression. written on February 18, 2017

The gradient descent function

How to find the minimum of a function using an iterative algorithm. written on February 05, 2017

Experimenting naive EUR/USD algo-trading

What happens when you blindly trade with a very dumb script in the year range 2000-2015. written on June 08, 2016

Linear regression with one variable

Finding the best-fitting straight line through points of a data set. written on April 01, 2016

Introduction to machine learning

What machine learning is about, types of learning and classification algorithms, introductory examples. written on March 12, 2016

Cumulative distribution function (CDF)

The probability that a random variable X will be found to have a value less than or equal to x. written on December 19, 2015

A volatility analysis on EUR/USD currency pair from 2000 to 2015

When the price of the EUR/USD cross is more volatile? written on December 11, 2015

The Central Limit theorem

Experiments on the fundamental theorem that explains why many distributions tend to be close to the normal distribution. written on November 28, 2015

The Normal distribution

The most famous kind of distribution and its relationship with the real world. written on November 06, 2015

Probability distributions

An overview of basic probability concepts, histograms, discrete/continuous variables. written on October 16, 2015

Random variables

How do they work, the differences between discrete and continuous ones, how to use them in probability. written on September 26, 2015

The Standard Deviation

Measuring the variability! written on August 30, 2015


Or the variability from an average value. written on August 21, 2015

Differences between a sample and a population

How do those relate to each other? written on August 21, 2015

Percentiles and quantiles

Basic tools to split and analyze data sets. written on August 06, 2015

Averages: mean, median, mode, range

Basic statistical concepts. written on July 31, 2015