Logistic regression is a predictive modelling algorithm that is used when the Y variable is binary categorical. That is, it can take only two values like 1 or 0. The goal is to determine a mathematical equation that can be used to predict the probability of event 1. Once the equation is established, it can … Continue reading Logistic Regression – A complete Tutorial

# Category: Machine Learning

# Linear Regression In Pictures

What is linear regression? Suppose you are thinking of selling your home. Different sized homes around you have sold for different amounts: Your home is 3000 square feet. How much should you sell it for? You have to look at the existing data and predict a price for your home. This is called linear regression. … Continue reading Linear Regression In Pictures

# Deep Learning Resources

Online Courses Andrew Ng’s Machine-Learning Class on Coursera Geoff Hinton’s Neural Networks Class on Coursera (2012) U. Toronto: Introduction to Neural Networks (2015) Yann LeCun’s NYU Couse Ng’s Lecture Notes for Stanford’s CS229 Machine Learning Nando de Freitas’s Deep Learning Class at Oxford (2015) Andrej Karpathy’s Convolutional Neural Networks Class at Stanford Patrick Winston’s Introduction … Continue reading Deep Learning Resources

# Summarize whole paragraph to sentence by Extractive Approach

To catch a quick idea of a long document, we will always to do a summarization when we read an article or book. In English, the first (or first two) sentence(s) of each article has a very high chance of representing the whole article. Of course, the topic sentence can be the last sentence in … Continue reading Summarize whole paragraph to sentence by Extractive Approach

# Docker in a Nutshell

I want to start to tackle two very important questions that we are going to be answering throughout this blog post. The two important questions are: What is Docker? Why do we use Docker? Let’s answer first Why we do use Docker by going through a quick little demo right now. Let’s have a look at this … Continue reading Docker in a Nutshell

# Introduction to Natural Language Processing with NLTK

What is Natural Language Processing? Natural Language Processing (NLP) helps computers (machines) "read and understand" text or speech by simulating human language abilities. However, in recent years, NLP has grown rapidly because of an abundance of data. Given that more and more unstructured data is available, NLP has gained immense popularity. Prerequisites Python 3.+ Jupyter Notebook Natural … Continue reading Introduction to Natural Language Processing with NLTK

# How to Create an ARIMA Model for Time Series Forecasting in Python

A popular and widely used statistical method for time series forecasting is the ARIMA model. ARIMA is an acronym that stands for AutoRegressive Integrated Moving Average. It is a class of model that captures a suite of different standard temporal structures in time series data. In this tutorial, you will discover how to develop an … Continue reading How to Create an ARIMA Model for Time Series Forecasting in Python

# The king that graph theory discovered

One morning in August 2012 in a car park in Leicester in the English midlands, a mechanical digger was starting to cut into the concrete surface. A number of interested spectators were present, hoping against hope that something amazing but highly improbable might occur. Some rugged detective work had led a group of amateur and … Continue reading The king that graph theory discovered

# Analyzing Facebook posts and activity using Topic Modelling and other NLP methods

In April, I permanently deleted my Facebook presence. I joined in 2008 and was fairly active over the years. In the process of deleting my account, I downloaded all my data. I couldn’t resist asking myself: what does this digital time capsule tell me about a decade of my life? And what hints does it … Continue reading Analyzing Facebook posts and activity using Topic Modelling and other NLP methods

# How does Machine Learning work?

In this article, we will use a simple example to illustrate the underlying process of learning from positive and negative examples, which is the simplest form of classification learning. Learning from a training set Imagine that a company has a recruiting process which looks at many thousands of applications and separates them into two groups — those who … Continue reading How does Machine Learning work?