This article was written by Johannes Rieke.
A very lightweight tutorial to object detection in images. We will bootstrap simple images and apply increasingly complex neural networks to them. In the end, the algorithm will be able to detect multiple…Continue
Added by Andrea Manero-Bastin on December 24, 2020 at 12:28pm — No Comments
Apache Flink is an open-source stream processing framework. It is widely used by a lot of companies like Uber, ResearchGate, Zalando. At its core, it is all about the processing of stream data coming…Continue
Added by Igor Bobriakov on February 6, 2020 at 8:00am — No Comments
In this notebook, we try to predict the positive (label 1) or negative (label 0) sentiment of the sentence. We use the UCI Sentiment Labelled Sentences Data Set.
Sentiment analysis is very useful in many areas.…Continue
Kubernetes is a technology that allows us to isolate an application. That is good but how can we scale this? Of course, we should create new containers.
But, how many containers should we have at the same time? How many…Continue
Added by Igor Bobriakov on January 21, 2020 at 7:30am — No Comments
When trend and seasonality is present in a time series, instead of decomposing it manually to fit an ARMA model using the Box Jenkins method, another very popular method is to use the seasonal autoregressive integrated moving average (SARIMA) model which is a generalization of an ARMA model. SARIMA models are denoted SARIMA(p,d,q)(P,D,Q)[S], where S refers to the number of periods in each season, d is the degree of differencing (the number of times the…
I’m sure you’ve probably heard about the 2018 FIFA Football World Cup in Russia everywhere during the last few months. And, if you are a techy too, I guess you also have realized that Machine Learning and Artificial Intelligence are buzzwords too. So, what better way to get ready for the World Cup than by practicing in a project that combines these two hot…Continue
Added by Regiane Folter on March 28, 2018 at 4:30am — No Comments
Principal Component Analysis (PCA) is a technique used to find the core components that underlie different variables. It comes in very useful whenever doubts arise about the true origin of three or more variables. There are two main methods for performing a PCA: naive or less naive. In the naive method, you first check some conditions in your data which will determine the essentials of the analysis. In the less-naive method, you set the those yourself,…Continue
Added by Pablo Bernabeu on September 6, 2017 at 1:30pm — No Comments
This is a tutorial to show how to implement dashboards in R, using the new "flexdashboard" library package.
this new library leverages these libraries and allows us to create some stunning dashboards, using interactive graphs and text. What I loved the most, was the “storyboard” feature that allows me to present content in Tableau-style frames. Please note that for this you need to create RMarkdown (.Rmd) files and insert the code using the…Continue
[The goal of this page]
When I have read all R introductions, the books were filled with just instructions. The goal of R is to solve our real life problem. That's why I want to minimize this page. In the real though, we need to understand some key concepts that might be useful for you to tackle the real life problem. Here's basic data structures and data manipulation method.
Still, I believe the best way to learn R programming language is to tackle the real life…
Ggplot2 is the most elegant and aesthetically pleasing graphics framework available in R. It has a nicely planned structure to it. This tutorial focusses on exposing this underlying structure you can use to make any ggplot. But, the way you make plots in ggplot2 is very different from base graphics making the learning curve steep. So leave what you know about base graphics behind and follow along. You are just 5…Continue