Von Liechtenstein Design with Data: A Guide to A/B Testing interaction-design.org How do you know your design choices actually improve the user experience of your products and services? You shouldn’t rely on your instincts alone—you …

Von Liechtenstein Principal Component Analysis in R - Walk Through | Machine Learning dimensionless.in - Samadrita Ghosh Principal Component Analysis or PCA is one of the simplest and fundamental techniques used in machine learning. It is perhaps one of the oldest …

Von Liechtenstein How to Develop an Information Maximizing GAN (InfoGAN) in Keras machinelearningmastery.com - Jason Brownlee Tweet Share ShareThe Generative Adversarial Network, or GAN, is an architecture for training deep convolutional models for generating synthetic …

Von Liechtenstein More datasets for teaching data science: The expanded dslabs package simplystatistics.org IntroductionWe have expanded the dslabs package, which we previously introduced as a package containing realistic, interesting and approachable …

Von LiechtensteinStochastic search and joint fine-mapping increases accuracy and identifies previously unreported associations in immune-mediated nature.com - Jennifer L. Asimit, Daniel B. Rainbow, Mary D. Fortune, Nastasiya F. Grinberg, Linda S. Wicker, Chris Wallace Thousands of genetic variants are associated with human disease risk, but linkage disequilibrium (LD) hinders fine-mapping the causal variants. Both …

Von LiechtensteinIcon version of the Flipboard logo Collinearity in Bayesian models columbia.edu - Andrew We were having a debate about how much of a problem collinearity is in Bayesian models. I was arguing that it is not much of a problem. Imagine we …

Von Liechtenstein 7 Fundamental Steps to Complete a Data Project dataiku.com - alivia.smith@dataiku.com (Alivia Smith) It's hard to know where to start once you’ve decided that yes, you want to dive into the fascinating world of data and AI. Just looking at all the …

Von Liechtenstein What if that regression-discontinuity paper had only reported local linear model results, and with no graph? columbia.edu - Andrew We had an interesting discussion the other day regarding a regression discontinuity disaster. In my post I shone a light on this fitted model: Most of …

Von Liechtenstein Moving beyond P values: data analysis with estimation graphics nature.com - Joses Ho, Tayfun Tumkaya, Sameer Aryal, Hyungwon Choi, Adam Claridge-Chang The Matlab, Python and R packages are available on GitHub (https://github.com/ACCLAB/DABEST-python) and are licensed under the BSD 3-Clause Clear …

Von LiechtensteinUX Design Heuristic Evaluation: How to Conduct a Heuristic Evaluation interaction-design.org Learn to conduct a heuristic evaluation on any given user interface design. This article will teach you how to generate and conduct your own …

Von LiechtensteinData Science A Comprehensive Introduction to Data Wrangling | Blog| Dimensionless dimensionless.in - Priyanka Gupta Data wrangling, in simpler terms, it is the process of transforming raw data into another format to make it more suitable for analytics. It may …

Von Liechtenstein (Markov chain) Monte Carlo doesn’t “explore the posterior” columbia.edu - Bob Carpenter [Edit: (1) There’s nothing dependent on Markov chain—the argument applies to any Monte Carlo method in high dimensions. (2) No, (MC)MC is not not …

Von Liechtenstein Transposing Excel Data Turns a Spreadsheet Mess Into a Big 'ol Success Lifewire - Ryan Dube Excel is a powerful tool for analyzing data, but some things like flipping cells in a row or column can be a real hassle. There's the slow manual …

Von Liechtenstein A Comprehensive Guide To R For Data Science | Data Science Using R codementor.io - Zulaikha In this R for Data Science blog, you will be able to understand the importance of Data Science and its implementation using the R language.

Von Liechtenstein A Beginner’s Guide To Genetic Algorithms analyticsindiamag.com - Ram Sagar Everything in this universe is governed by one principle- to achieve equilibrium. Things appear and disappear in this process. Life appeared out of …

Von Liechtenstein Essential Math And Statistics For Data Science Tutorial codementor.io - Zulaikha In this blog post, you will understand the importance of Math and Statistics for Data Science and how they can be used in Data Science.

Von LiechtensteinIcon version of the Flipboard logo Tutorial: Poisson Regression in R dataquest.io - Hafsa Jabeen Poisson Regression can be a really useful tool if you know how and when to use it. In this tutorial we're going to take a long look at Poisson …

Von Liechtenstein Bias Variance Trade Off | Blog | Dimesionless Technologies dimensionless.in - Jagrati Valecha Deep Learning is highly empirical domain which majorly focusses on fine tuning the various parameters. The choice of these parameters defines the …

Von Liechtenstein Implementing The Perceptron Algorithm From Scratch In Python hackernoon.com - NiranjanKumar In this post, we will see how to implement the perceptron model using breast cancer data set in python. A perceptron is a fundamental unit of the …

Von Liechtenstein What is Predictive Model Performance Evaluation | Blog dimensionless.in - Kartik Singh Evaluation metrics have a correlation with machine learning tasks. The tasks of classification, regression, ranking, clustering, topic modelling, …

Von LiechtensteinAlgorithms Understanding ROC Curves with Python stackabuse.com - Guest Contributor In the current age where Data Science / AI is booming, it is important to understand how Machine Learning is used in the industry to solve complex …

Von Liechtenstein Perceptron — Deep Learning Basics hackernoon.com - Niranjan Kumar Perceptron is a fundamental unit of the neural network which takes weighted inputs, process it and capable of performing binary classifications. In …

Von Liechtenstein How to Train a Decision Tree Classifier for Churn Prediction | Blog dimensionless.in - Kartik Singh In computer science, Decision tree learning uses a decision tree (as a predictive model) to go from observations about an item to conclusions about …

Von Liechtenstein The knowns and unknowns framework for design thinking uxdesign.cc - AJ Justo On the 12th of February 2002, Donald Rumsfeld, back then Secretary of State of the US, used an until then little known framework to help him in …

Von Liechtenstein Supervised Learning: Bayesian Learning dev.to - shawn swyx wang 🇸🇬 This is the 10th in a series of class notes as I go through the Georgia Tech/Udacity Machine Learning course. The class textbook is Machine Learning …

Von Liechtenstein Controlling False Discoveries in Large-Scale Experimentation: Challenges and Solutions berkeley.edu - Daniel Seita “Scientific research has changed the world. Now it needs to change itself.” There has been a growing concern about the validity of scientific …

Von Liechtenstein How It Feels to Learn Data Science in 2019 hackernoon.com - Thomas Nield Wait, what? So I just have to buy a Tableau license and I’m now a data scientist? Okay, let’s just take that sales pitch with a grain of salt. I may …

Von LiechtensteinData Science State of PPL: How are Bayesian methods used in industry? peadarcoyle.com I recently put together a survey of over 100 data scientists and analysts. There’ll be a report coming super soon, but before then I wanted to share …

Von Liechtenstein Principal Component Analysis — Unsupervised Learning Model hackernoon.com - Packt_Pub Learn how to train and evaluate an unsupervised machine learning model — principal component analysis in this article by Jillur Quddus, a lead …