Data Science Austria

Autoencoders: Deep Learning with TensorFlow’s Eager API | Data Stuff

We are so deep. Source: Pixabay. Deep Learning has revolutionized the Machine Learning scene in the last years. Can we apply it to image compression? How well can a Deep Learning algorithm reconstruct pictures of kittens? What’s an autoencoder? Today we’ll find the answers to all of those questions. Image Compression: … Read moreAutoencoders: Deep Learning with TensorFlow’s Eager API | Data Stuff

Linear programming and discrete optimization with Python using PuLP

Linear and integer programming are key techniques for discrete optimization problems and they pop up pretty much everywhere in modern business and technology sectors. We will discuss how to tackle such problems using Python library PuLP and get a fast and robust solution. Introduction Discrete optimization is a branch of … Read moreLinear programming and discrete optimization with Python using PuLP

Making the Mueller Report Searchable with OCR and Elasticsearch

April 18th marked the full release of the Mueller Report — a document outlining the investigation of potential Russian interference in the 2016 presidential election. Like most government documents it is long (448 pages), and would be painfully tedious to read. Source To make matters worse, the actual PDF download is basically … Read moreMaking the Mueller Report Searchable with OCR and Elasticsearch

3 Awesome Visualization Techniques for every dataset

Categorical Correlation with Graphs: In Simple terms, Correlation is a measure of how two variables move together. For example, In the real world, Income and Spend are positively correlated. If one increases the other also increases. Academic Performance and Video Games Usage is negatively correlated. Increase in one predicts a decrease … Read more3 Awesome Visualization Techniques for every dataset

Calculating the Semantic Brand Score with Python

Data Collection and Text Pre-processing The calculation of the Semantic Brand Score requires combining methods and tools of text mining and social network analysis. Figure 1 illustrates the main preliminary steps, which comprise data collection, text pre-processing and construction of word co-occurrence networks. Figure 1 — From Texts to Networks For this introductory … Read moreCalculating the Semantic Brand Score with Python

Explaining probability plots

Source In this article I would like to explain the concept of probability plots — what they are, how to implement them in Python and how to interpret the results. 1. Introduction You might have already encountered one type of probability plots —Q-Q plots — while working with linear regression. One of the assumptions of … Read moreExplaining probability plots

Create a complete Machine learning web application using React and Flask

I have always wanted to develop a complete Machine learning application where I would have a UI to feed in some inputs and the Machine learning model to predict on those values. Last week, I did just that. In the process, I created an easy to use template in React … Read moreCreate a complete Machine learning web application using React and Flask