# Data Science Austria

## A short guide to using Docker for your data science environment

WHY One of the most time consuming part of starting your work on a new system/starting a new job or just plain sharing your work is the variation of tools available (or lack thereof) due to differences in hardware/software/security policies and what not. Containerization has risen up in recent years … Read moreA short guide to using Docker for your data science environment

## I Can Be Your Heroku, Baby

Deploying a Python app in Heroku! Do you like Data Science? <Shakes head up and down> Do you like Data Science DIY deployment? <Shakes head left and right> Me neither. One of the most frustrating parts of early data science learning or personal work is deploying an app through free cloud … Read moreI Can Be Your Heroku, Baby

## Exploratory Data Analysis (EDA) techniques for kaggle competition beginners

A hands on guide for beginners on EDA and Data Science competitions Exploratory Data Analysis (EDA) is an approach to analysing data sets to summarize their main characteristics, often with visual methods. Following are the different steps involved in EDA : Data Collection Data Cleaning Data Preprocessing Data Visualisation Data Collection … Read moreExploratory Data Analysis (EDA) techniques for kaggle competition beginners

## PyTorch 101 for Dummies like Me

Nov 5, 2018 What is PyTorch? It’s a Python-based package to serve as a replacement for Numpy arrays and to provide a flexible library forDeep Learning Development Platform. As for the why I prefer PyTorch over TensorFLow can be learned from this Fast AI’s blog post for the reason to switch … Read morePyTorch 101 for Dummies like Me

## Introduction to Linear Regression in Python

Basic concepts and mathematics There are two kinds of variables in a linear regression model: The input or predictor variable is the variable(s) that help predict the value of the output variable. It is commonly referred to as X. The output variable is the variable that we want to predict. … Read moreIntroduction to Linear Regression in Python

## The intuition behind Shannon’s Entropy

Now, back to our formula 3.49: The definition of Entropy for a probability distribution (from The Deep Learning Book) I(x) is the information content of X. I(x) itself is a random variable. In our example, the possible outcomes of the War. Thus, H(x) is the expected value of every possible information. … Read moreThe intuition behind Shannon’s Entropy

## Forecasting Exchange Rates Using ARIMA In Python

Sep 29, 2018 Nearly all sectors use time series data to forecast future time points. Forecasting future can assist analysts and management in making better calculated decisions to maximise returns and minimise risks. I will be demonstrating how we can forecast exchange rates in this article. If you are new … Read moreForecasting Exchange Rates Using ARIMA In Python

## Doing XGBoost hyper-parameter tuning the smart way — Part 1 of 2

Aug 29, 2018 Picture taken from Pixabay In this post and the next, we will look at one of the trickiest and most critical problems in Machine Learning (ML): Hyper-parameter tuning. After reviewing what hyper-parameters, or hyper-params for short, are and how they differ from plain vanilla learnable parameters, we introduce … Read moreDoing XGBoost hyper-parameter tuning the smart way — Part 1 of 2

## Automatic Image Quality Assessment in Python

Aug 28, 2018 Image quality is a notion that highly depends on observers. Generally, it is linked to the conditions in which it is viewed; therefore, it is a highly subjective topic. Image quality assessment aims to quantitatively represent the human perception of quality. These metrics are commonly used to analyze … Read moreAutomatic Image Quality Assessment in Python

## Google’s AutoML Killer: Auto-Keras Opensource Automated ML

Auto-Keras is an open source software library for automated machine learning (AutoML). It is developed by DATA Lab at Texas A&M University and community contributors. The ultimate goal of AutoML is to provide easily accessible deep learning tools to domain experts with limited data science or machine learning background. Auto-Keras … Read moreGoogle’s AutoML Killer: Auto-Keras Opensource Automated ML