Singularity Artificial Intelligence Detects Heart Failure From One Heartbeat With 100% AccuracyForbes - Nicholas FearnDoctors can detect heart failure from a single heartbeat with 100% accuracy using a new artificial intelligence-driven neural network. That’s according to a recent study published in Biomedical Signal

Statistics Probability Learning II: How Bayes’ Theorem is applied in Machine Learningtowardsdatascience.com - Jaime Zornoza Learn how Bayes Theorem is in Machine Learning for classification and regression! In the previous post we saw what Bayes’ Theorem is, and went through …

Driving Autonomous Cars: Deep Learning and Computer Vision in Pythonoreilly.com Learn OpenCV, Keras, object and lane detection, and traffic sign classification for self-driving cars. Learn complex topics such as artificial …

Data Science HyperOpt: Bayesian Hyperparameter Optimizationdominodatalab.com This article covers how to perform hyperparameter optimization using a sequential model-based optimization (SMBO) technique implemented in the …

Statistics Bayesian Priors and Regularization Penaltiestowardsdatascience.com - Ray Heberer Bayesian methods of performing machine learning offer several advantages over their counterparts, notably the ability to estimate uncertainty and the …

Machine Learning 6 Important Steps to build a Machine Learning Systemtowardsdatascience.com - Rahul Agarwal There are a lot of things to consider while building a great machine learning system. But often it happens that we as data scientists only worry …

Mathematics Data Science with no Mathtowardsdatascience.com - Rich Folsom This is an addendum to my last article, in which I had to add a caveat at the end that I was not a mathematician, and I was new at Python. I added …

Probability Understanding Boxplotstowardsdatascience.com - Michael Galarnyk The image above is a boxplot. A boxplot is a standardized way of displaying the distribution of data based on a five number summary (“minimum”, first …

Data Science Transfer Learning - from the ground upfastforwardlabs.com Machine learning enables us to build systems that can predict the world around us: like what movies we’d like to watch, how much traffic we’ll …

Deep Learning Scientists develop a deep learning method to solve a fundamental problem in statistical physicsphys.org A team of scientists at Freie Universität Berlin has developed an Artificial Intelligence (AI) method that provides a fundamentally new solution of …

FlipboardIcon version of the Flipboard logoData Science Calibration and sharpness? « Statistical Modeling, Causal Inference, and Social Sciencecolumbia.edu I really liked this paper, and am curious what other people think before I base a grant application around applying Stan to this problem in a …

Statistics Probability Learning IV : The Math Behind Bayestowardsdatascience.com - Jaime Zornoza After the two previous posts about Bayes’ Theorem, I got a lot of requests asking for a deeper explanation on the maths behind the regression and …

Google AI Google launches TensorFlow machine learning framework for graphical dataVentureBeat - Khari JohnsonGoogle today introduced Neural Structured Learning (NSL), an open source framework that uses the Neural Graph Learning method for training neural networks with graphs and structured data. NSL works with

Workflow Workflow systems turn raw data into scientific knowledgenature.com - Jeffrey M. Perkel How workflow tools can make your computational methods portable, maintainable, reproducible and shareable. Reinventing the wheel is pointless, but for …

OCR Premade AI in the Cloud with Pythontowardsdatascience.com - Diego Penilla Now that we’ve been through the boring stuff, we are ready to use the resources and see what they are capable of. Creating resources has given us …

Business Analytics Online Course: Business Analytics | Harvard Business School Onlinehbs.edu Janice Hammond is the Jesse Philips Professor of Manufacturing and Senior Associate Dean for Culture and Community at Harvard Business School. She …

Machine Learning Markov Networks: Undirected Graphical Modelstowardsdatascience.com - Kushal Vala This article briefs you about Markov Networks which falls under the family of Undirected Graphical Models (UGM). This article is a follow-up to Bayesian …

Data Management Everything a Data Scientist Should Know About Data Management*towardsdatascience.com - Phoebe Wong To be a real “full-stack” data scientist, or what many bloggers and employers call a “unicorn,” you’ve to master every step of the data science …

Unsupervised Learning Applied Unsupervised Learning with Pythonoreilly.com Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data Learn how to select the most …

FlipboardIcon version of the Flipboard logoProbability Genetics and Statistical Analysis | Learn Science at Scitablenature.com One of Pearson's most significant achievements occurred in 1900, when he developed a statistical test called Pearson's chi-square (Χ2) test, also …

Coin Collecting Fun with the Binomial Distributiontowardsdatascience.com - Tony Yiu Understanding the Lesser Known Cousin of the Normal Distribution and How to Apply It Everyone knows and loves the normal distribution. It is used in a …

Google Drive 14 incredibly useful things you didn’t know Google Drive could doFast Company - JR RaphaelMake Google’s online storage service better than ever with these unexpected options and productivity-boosting add-ons. If you’re thinking of Google Drive as a mere place to plop your files, you’re missing

The Brain A Mathematical Model Unlocks the Secrets of VisionQuanta Magazine - Kevin Hartnett Mathematicians and neuroscientists have created the first anatomically accurate model that explains how vision is possible. This is the great mystery …

Artificial Intelligence Google's AutoML Reminds Us That Machines Are Increasingly Helping To Build Our AI AdvancesForbes - Kalev LeetaruTimeline of accuracy advances in ImageNet image recognition showing the leap from human to machine-generated models. (Google). In the early days of deep learning, models were bespoke creations hand-built

NAACL ’19 Notes: Practical Insights for Natural Language Processing Applications — Part Imedium.com - Nikita Zhiltsov • in general, the choice of a pre-training task and an end task is coupled, i.e., closer pre-training mimics the target task, better results; • language …

A new tool uses AI to spot text written by AIMIT Technology Review - Will Knight AI algorithms can generate text convincing enough to fool the average human—potentially providing a way to mass-produce fake news, bogus reviews, and …

Towards algorithmic analytics for large-scale datasetsnature.com - Danilo Bzdok, Thomas E. Nichols, Stephen M. Smith Efron, B. Large-scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction Vol. 1 (Cambridge Univ. Press, 2012). Efron, B. & …

Automated and Interpretable Machine LearningSlideShare - Francesca Lazzeri, PhDAutomated machine learning is based on a breakthrough from Microsoft’s Research Division. The approach combines ideas from collaborative filtering and Bayesian optimization to search an enormous space

Invariant Risk Minimization: An Information Theoretic Viewinference.vc - Ferenc Huszar There are three (sets of) observable variables: $E$, the environment index, $X$, the features describing the datapoint and $Y$, the label we wish to …