Every two weeks, we find the most interesting data science links from around the web and collect them in Data Science Briefings, the DataMiningApps newsletter. Subscribe now for free if you want to be the first to get up to speed on interesting resources.
- Google’s DeepMind defeats legendary Go player Lee Se-dol in historic victory
A huge milestone has just been reached in the field of artificial intelligence: AlphaGo, a program developed by Google’s DeepMind unit, has defeated legendary Go player Lee Se-dol; what an exciting match! Everyone (Wired, The Verge, Nature) seems to be covering it.
- Engineers Shouldn’t Write ETL: A Guide to Building a High Functioning Data Science Department
Incredibly article which goes into depth regarding data science team composition and management, definitely worth a read!
- Beyond the hype: Why competitive advantage from analytics is declining and what to do about it
The 2016 Data & Analytics Report by MIT Sloan Management Review and SAS finds that analytics is now a mainstream idea, but not a mainstream practice. Few companies have a strategic plan for analytics or are executing a strategy for what they hope to achieve with analytics. Organizations achieving the greatest benefits from analytics ensure the right data is being captured, and blend information and experience in making decisions.
- Big Data Analysis Is Changing the Nature of Sports Science
When it’s possible to record the exact movements of players in team games such as football, can algorithms crunch this data to provide meaningful insight?
- An AI with 30 Years’ Worth of Knowledge Finally Goes to Work
Having spent the past 31 years memorizing an astonishing collection of general knowledge, the artificial-intelligence engine created by Doug Lenat is finally ready to go to work. Lenat’s creation is Cyc, a knowledge base of semantic information designed to give computers some understanding of how things work in the real world.
- Deep Q-Learning (Space Invaders)
“Ever since I learned about neural networks playing Atari games I wanted to reimplemnted it and learn how it works. Below you can see an AI playing Space Invaders. I trained it during my batch at Recurse Center on little over 50M frames.”
- Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis — Torch Implementation
This is the torch implementation for paper “Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis”. This algorithm is for un-guided image synthesis (for example, classical texture synthesis) and guided image synthesis (for example, transfer the style between different images).
- Neural Doodle
Use a deep neural network to borrow the skills of real artists and turn your two-bit doodles into masterpieces! This project is an implementation of Semantic Style Transfer (Champandard, 2016), based on the Neural Patches algorithm (Li, 2016).
- Diagnosing Heart Diseases with Deep Neural Networks
Congrats to our colleagues from Ghent: the Second National Data Science Bowl, a data science competition where the goal was to automatically determine cardiac volumes from MRI scans, has just ended. 4 members from the Data Science lab at Ghent University in Belgium participated and finished 2nd!
- Police Will Soon Be Watched by Algorithms That Try to Predict Misconduct. Is That a Good Thing?
Police in Charlotte, North Carolina, are set to become guinea pigs for a new high-tech approach to improving relations between cops and citizens. The Charlotte-Mecklenburg police department is working with University of Chicago researchers to create software that tries to predict when an officer is likely to have a bad interaction with someone.
- How to replace a pie chart
“The problem with a lot of pie-chart bashing (and most “chart-shaming,” in fact) is that people don’t follow up with a better alternative. So here I’ll show how I would have created a different graph (using R and ggplot2) to communicate the same information.”
- Intuition in machine learning
“It has been particularly refreshing to hear Andrew Ng recognize that the inner workings of ML algorithms often don’t make intuitive sense. What struck me is that there doesn’t seem to be a single way to learn machine learning concepts— we create an intuitive understanding of algorithms by approaching them from different perspectives.”
- XGBoost4J: Portable Distributed XGBoost in Spark, Flink and Dataflow
“We introduce the new-brewed XGBoost4J, XGBoost for JVM Platform. We aim to provide the clean Java/Scala APIs and the integration with the most popular data processing systems developed in JVM-based languages.”
- Lift analysis – A data scientist’s secret weapon
“I want to dig a bit deeper into another valuable evaluation technique, generally referred to as lift analysis.”
- IRMUK Data Governance Conference 2016 on May 16-19 in London
A must attend!
- Festschrift Conference in Honour of prof. Lyn Thomas in the Year of His 70th Birthday
This one-day conference is convened to mark Professor Lyn Thomas’s research career in the fields of credit scoring and operations research and will feature a series of invited speakers on topics linked to his unique contributions in both fields.
