02/05/19 Best Practices for Preparing and Augmenting Image Data for Convolutional Neural Networks
02/05/19 Putting vision models to the test
02/05/19 The AI disconnect in the financial services industry
02/05/19 Intelligent Big Data Lake Governance
02/05/19 Managing machine learning
02/05/19 Machine Learning Internship: Standing on the shoulders of giants
02/05/19 Using AI and Social Media to Detect Noisy Areas
02/05/19 Online Learning
02/05/19 Parasoft takes on test data with upgraded SOAtest and Virtualize
02/05/19 Data Warehouses: Past, Present and Future
02/05/19 Ethics in AI: When Will We Progress?
02/05/19 Optimizing Kafka Streams Applications
02/05/19 Get Off Your Lazy NAS With Intelligent Data Management
02/05/19 New approach could accelerate efforts to catalogue vast numbers of cells
01/05/19 MIT Solve announces $1.25 million in funding for 2019 Solver teams
01/05/19 Setting Up and Running Apache Kafka on Windows OS
01/05/19 Build and Install Hadoop on Windows With Native Binaries
01/05/19 Kafka Internals: FAQs
01/05/19 A comprehensive map of how Alzheimer’s affects the brain
01/05/19 Kafka Technical Overview
01/05/19 FPGAs Open Gates in Machine Learning
01/05/19 J-Clinic names 18 grant recipients from across Institute
01/05/19 Predicting Mortality
01/05/19 Replacing Clunky Data Dashboards With Chatbots
01/05/19 How Related Are Your Documents?
01/05/19 Machine Revolution!? [Comic]
01/05/19 PyDev of the Week: Neil Muller
01/05/19 Graph clustering while minimizing the maximum intra-cluster edge weight
01/05/19 From science class to the stock exchange
30/04/19 A Gentle Introduction to the ImageNet Large Scale Visual Recognition Challenge (ILSVRC)
30/04/19 Liberty Mutual Insurance joins MIT's Quest for Intelligence
30/04/19 The quest to understand human society scientifically
30/04/19 Big Data Trends to Look Out for in 2019
30/04/19 ML seminar, Tue 28 May, 3:30pm
30/04/19 How Can AI Be Used in Schools?
30/04/19 Sending External Requests: Misty as a Security Guard: Part 2
30/04/19 Working With Face Recognition: Misty as a Security Guard: Part 1
30/04/19 Taking Pictures: Misty as a Security Guard: Part 3
30/04/19 Understanding Object Detection Using YOLO
30/04/19 Exploring And Attacking Neural Networks With Activation Atlases
30/04/19 Why Your Spark Apps Are Slow Or Failing, Part II: Data Skew and Garbage Collection
30/04/19 ML seminar, Fri 17 May, 2pm
30/04/19 Red Pepper Chef: From New Training Data to Deployed System in a Few Lines of Code
30/04/19 A Closer Look at Deep Policy Gradients (Part 3: Landscapes and Trust Regions)
29/04/19 Big Data and Analytics Integration
29/04/19 How to Install Anaconda on ECS
29/04/19 Is That Canary In The Datacenter Feeling Dizzy?
29/04/19 Python at Netflix
29/04/19 For better deep neural network vision, just add feedback (loops)
29/04/19 Data Integration vs. Data Pipeline: What's the Difference?
29/04/19 Build It Yourself: Chatbot API With Keras/TensorFlow Model
29/04/19 Lyft’s Data Platform with Li Gao
29/04/19 What Is AI's Role in Your Business' Future?
29/04/19 Can Social Networks Predict Whether an Employee Will Quit?
29/04/19 3Q: Assessing MIT’s computing infrastructure needs
29/04/19 The Algorithm That Made the Black Hole Picture
28/04/19 A Gentle Introduction to 1×1 Convolutions to Reduce the Complexity of Convolutional Neural Networks
28/04/19 Tom's Tech Notes: What You Need to Know About Big Data [Podcast]
26/04/19 Nanoparticles take a fantastic, magnetic voyage
26/04/19 What Is a Data Pipeline?
26/04/19 Technically Speaking, What Is Data Governance?
26/04/19 Things to Understand Before Implementing ETL Tools
26/04/19 Working Next to Robots
26/04/19 Text-Mined Knowledge Graphs — Beyond Text Mining
26/04/19 The Deep End of Deep Learning
25/04/19 How to Implement VGG, Inception and ResNet Modules for Convolutional Neural Networks from Scratch
25/04/19 Mistakes to Avoid When Adopting Salesforce Data Migration
25/04/19 MuseNet
25/04/19 Improving Uber’s Mapping Accuracy with CatchME
25/04/19 Product Feature Spotlight: Review
25/04/19 Writing to a CSV File From Multiple Threads
25/04/19 State privacy laws to watch
25/04/19 Learn TensorFlow: Linear Regression
25/04/19 Map and Filter Function in Python
25/04/19 Are Natural Mathematical Problems Bad Problems?
24/04/19 Deep Learning, Part 3: Too Deep or Not Too Deep? That is the Question.
23/04/19 Generative Modeling with Sparse Transformers
23/04/19 An Invitation to a Conference: Visions in Mathematics towards 2000
23/04/19 Improving security as artificial intelligence moves to smartphones
23/04/19 Nine universities team up to create global infrastructure for digital academic credentials
23/04/19 NVIDIA's AI Creates Beautiful Images From Your Sketches
23/04/19 Forums address MIT’s plans to reshape its computer science education
22/04/19 The Role of Structure in AI
21/04/19 $\exists \mathbb R$ and IP
21/04/19 A Gentle Introduction to Pooling Layers for Convolutional Neural Networks
20/04/19 How Do Neural Networks Memorize Text?
19/04/19 Representer Point Selection for Explaining Deep Neural Networks
19/04/19 Preparing high schoolers for a tech-driven future
19/04/19 J-PAL North America’s newest initiative explores the work of the future
19/04/19 3Q: Setting academic parameters for the MIT Schwarzman College of Computing
19/04/19 Calling Python from Mathematica
18/04/19 A Gentle Introduction to Padding and Stride for Convolutional Neural Networks
18/04/19 Can science writing be automated?
17/04/19 Vivienne Sze wins Edgerton Faculty Award
17/04/19 MIT Program in Digital Humanities launches with $1.3 million Mellon Foundation grant
17/04/19 Jump-starting the economy with science
17/04/19 3Q: Structuring the MIT Schwarzman College of Computing
17/04/19 Four from MIT elected to American Academy of Arts and Sciences for 2019
17/04/19 Drishti: Deep Learning for Manufacturing with Krish Chaudhury
17/04/19 Giving robots a better feel for object manipulation
16/04/19 A Gentle Introduction to Convolutional Layers for Deep Learning Neural Networks
16/04/19 Robots that can sort recycling
16/04/19 Deep Learning, Part 2: Depth Charge
16/04/19 OpenAI GPT-2: An Almost Too Good Text Generator
16/04/19 Lyft Data Discovery with Tao Feng and Mark Grover
16/04/19 Improving the Supervised Learning Model using Python
16/04/19 A novel data-compression technique for faster computer programs
15/04/19 Brighterion Named Most Scalable Platform and Leader of the Contenders in Latest Aite Group Report
15/04/19 How to Train Your OpenAI Five
15/04/19 Building an Open Source Mixpanel Alternative. Part 2: Conversion Funnels
15/04/19 Protein Structure Deep Learning with Mohammed Al Quraishi
15/04/19 Mahalonobis Distance – Understanding the math with examples (python)
15/04/19 The Great Data Science Specialist vs. Generalist Debate
14/04/19 How to Use Test-Time Augmentation to Improve Model Performance for Image Classification
14/04/19 TR19-057 | Proof Complexity of Symmetry Learning in QBF | Joshua Blinkhorn, Olaf Beyersdorff
14/04/19 OpenAI Finals
13/04/19 datetime in Python – Simplified Guide with Clear Examples
12/04/19 What's So Hard About Cloth Simulations?
11/04/19 Five from MIT win 2019 Paul and Daisy Soros Fellowships for New Americans
11/04/19 How to Configure Image Data Augmentation When Training Deep Learning Neural Networks
11/04/19 Deep Learning, Part 1: Not as Deep as You Think
11/04/19 Exploring MARS and Getting back to Bayesics
11/04/19 3 Questions: Provost Martin Schmidt on building a new college
10/04/19 Machine Learning Joins with Arun Kumar
09/04/19 Open Questions about Generative Adversarial Networks
09/04/19 MIT spinout seeks to transform food safety testing
08/04/19 This Week in Machine Learning and AI: Implicit Self-Regularization
08/04/19 How to think about moonshot projects
08/04/19 Data privacy Twitter account
07/04/19 The Bitter Lesson - Compute Reigns Supreme
06/04/19 Learning in the Presence of Strategic Behavior (EC 2019 Workshop)
05/04/19 The evolving definition of a gene
05/04/19 Letter regarding the MIT Schwarzman College of Computing community forums in April
05/04/19 Driving toward success
05/04/19 AWS Compute with Deepak Singh
04/04/19 KSA meeting explores collaboration in 2019
04/04/19 Data with Ben Lorica
03/04/19 The power of play
03/04/19 The future of agriculture is computerized
03/04/19 Machine learning moves popular data elements into a bucket of their own
03/04/19 Advance boosts efficiency of flash storage in data centers
02/04/19 A Visual Exploration of Gaussian Processes
02/04/19 Beautiful Gooey Simulations, Now 10 Times Faster
02/04/19 Teaching machines to reason about what they see
01/04/19 Mixture of Variational Autoencoders - a Fusion Between MoE and VAE
01/04/19 SF Bay ACM Talk: Heavy Tailed Self Regularization in Deep Neural Networks
01/04/19 #59 Data Science R&D at TD Ameritrade
01/04/19 Inferring religion from fitness data
01/04/19 Statistical significance in hypothesis testing
31/03/19 Summer School on Randomness and Learning in Non-Linear Algebra
30/03/19 NeuroSAT: An AI That Learned Solving Logic Problems
30/03/19 Data Visualization using Bokeh package in Python
30/03/19 Unsupervised Learning k-means clustering algorithm in Python
29/03/19 Building Machine Learning Models via Comparisons
29/03/19 Changing the World – One Scientific Breakthrough at a Time
29/03/19 Putting topological data analysis in context
28/03/19 The Sweetness of a Bitter Lesson and Bringing ML and Healthcare Closer
28/03/19 Modeling unions of unbounded convex polyhedra exactly?
27/03/19 This AI Learned to “Photoshop” Human Faces
27/03/19 Linear Regression: A Technical Overview
27/03/19 Citizenship, Privacy, and the 2020 Census
27/03/19 ML seminar, Wed 3 Apr, 2pm
27/03/19 MIT receives $30 million to help address energy challenges in Egypt
26/03/19 Automating Linear Regressions with WhizzML & Python Bindings
26/03/19 OpenAI Five Finals
26/03/19 Facebook is free, but should it count toward GDP anyway?
26/03/19 10 Milestones in the History of Mathematics according to Nati and Me
25/03/19 Visualizing memorization in RNNs
25/03/19 New 3-D printing approach makes cell-scale lattice structures
25/03/19 Machine Learning Boosts Startups and Industry
25/03/19 Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…
25/03/19 #58 Critical Thinking in Data Science
25/03/19 3 Questions: Why are student-athletes amateurs?
25/03/19 The language model too dangerous to release
23/03/19 Google’s PlaNet AI Learns Planning from Pixels
23/03/19 Natural Language Processing using Python
22/03/19 Model learns how individual amino acids determine protein function
22/03/19 Programming Linear Regressions
21/03/19 Linear Regression in a few Clicks with the BigML Dashboard
21/03/19 Implicit Generation and Generalization Methods for Energy-Based Models
21/03/19 Building an Open Source Mixpanel Alternative. Part 1: Collecting and Displaying Events
20/03/19 “Particle robot” works as a cluster of simple units
20/03/19 Bigger Results from Smaller Data with Linear Regression
20/03/19 Women in Data Science conference unites global community of researchers and practitioners
19/03/19 Contrastive Unsupervised Learning of Semantic Representations: A Theoretical Framework
19/03/19 3Q: Sarah Williams on mapping urban transport
19/03/19 Using machine learning for medical solutions
18/03/19 Open access task force releases draft recommendations
18/03/19 Gulf Stream series wins Knight Science Journalism Program’s Inaugural Victor K. McElheny Award
18/03/19 Accessible Machine Learning through Data Workflow Management
18/03/19 Tim Berners-Lee named FT “Boldness in Business” Person of the Year
18/03/19 Ethics, computing, and AI: Perspectives from MIT
18/03/19 #57 The Credibility Crisis in Data Science
17/03/19 The Cathedral and the Bazaar
17/03/19 Liquid Splash Modeling With Neural Networks
15/03/19 MIT celebrates 50th anniversary of historic moon landing
15/03/19 Exercises in amazement: Discovering deep learning
15/03/19 Robot hand is soft and strong
14/03/19 Slowed Down Conferences and Even More Summer Schools
13/03/19 OpenAI Scholars Class of Spring '19
13/03/19 Data Science at Scale: A Conversation with Uber’s Fran Bell
13/03/19 Microgravity research after the International Space Station
12/03/19 GANPaint: An Extraordinary Image Editor AI
11/03/19 OpenAI LP
11/03/19 Product Feature Spotlight: Teach
11/03/19 Energy Market Machine Learning with Minh Dang and Corey Noone
11/03/19 #56 Data Science at AT&T Labs Research
11/03/19 AlphaStar
09/03/19 This Experiment Questions Some Recent AI Results
08/03/19 Students helping to make islands carbon neutral
08/03/19 A new way to calculate global intensive care unit mortality risk
08/03/19 Netlify with Mathias Biilmann Christensen
07/03/19 Combining artificial intelligence with their passions
07/03/19 US GDPR Coming Soon?
06/03/19 Activation Atlas
06/03/19 Introducing Activation Atlases
06/03/19 Big issues on the table at the MIT Sloan Sports Analytics Conference
06/03/19 Chernobyl: How bad was it?
05/03/19 Making a path to ethical, socially-beneficial artificial intelligence
05/03/19 Do Neural Networks Need To Think Like Humans?
05/03/19 Computing the future
05/03/19 Q&A: Meet the former all-star pitcher turned MIT student
05/03/19 Negotiating with infrastructure cyberterrorists
04/03/19 Neural MMO: A Massively Multiagent Game Environment
04/03/19 Solve launches 2019 global challenges
04/03/19 ML seminar, Wed 13 Mar, 2pm
04/03/19 #55 Getting Your First Data Science Job
04/03/19 Mini cheetah is the first four-legged robot to do a backflip
04/03/19 Are machine learning engineers the new data scientists?
03/03/19 Python Logging – Simplest Guide with Full Code and Examples
03/03/19 Accuracy of models using python
01/03/19 Addressing the promises and challenges of AI
01/03/19 For founders of new college of computing, the human element is paramount
01/03/19 Securing the “internet of things” in the quantum age
28/02/19 Lighting the path
28/02/19 Jupyter Notebooks and Modern Model Distribution
28/02/19 Reading the heartbeat of the road
28/02/19 The future of education in a world of pervasive computing
27/02/19 Taking the lead in shaping the future of computing and artificial intelligence
26/02/19 Impossibility Results in Fairness as Bayesian Inference
26/02/19 Problems with a Point: Exploring Math and Computer Science
26/02/19 Spinning Up in Deep RL: Workshop Review
26/02/19 Mathematics Professor Bonnie Berger honored with ISCB Senior Scientist Award
26/02/19 Supercomputers can spot cyber threats
26/02/19 What 126 studies say about education technology
26/02/19 Student challenges kick off celebration of MIT Stephen A. Schwarzman College of Computing
25/02/19 Using the HL7 FHIR Standard for Clinical Variation Management
25/02/19 Undark magazine wins George Polk Award for environmental reporting
25/02/19 Twenty-five ways in which MIT has transformed computing
25/02/19 #54 Women in Data Science
25/02/19 Interview with Alex Radovic, particle physicist turned machine learning researcher
23/02/19 Regression model in Machine Learning using Python
23/02/19 Matplotlib Histogram – How to Visualize Distributions in Python
22/02/19 Optimization and Gradient Descent on Riemannian Manifolds
22/02/19 Notes on Riemannian Geometry
22/02/19 An Overdue Post on AlphaStar, Part 2
22/02/19 An Overdue Post on AlphaStar, Part 1
21/02/19 Achieving greater efficiency for fast data center operations
21/02/19 Exploring the nature of intelligence
21/02/19 Uber Open Source: Catching Up with Fritz Obermeyer and Noah Goodman from the Pyro Team
21/02/19 Dan Huttenlocher named inaugural dean of MIT Schwarzman College of Computing
21/02/19 PlanetScale: Sharded Database Management with Jiten Vaidya and Dan Kozlowski
21/02/19 Preventing Fake News
20/02/19 Hiroshi Ishii wins Association for Computing Machinery SIGCHI Lifetime Research Award
20/02/19 Putting data privacy in the hands of users
19/02/19 Festival of Learning highlights innovation
19/02/19 AI Safety Needs Social Scientists
19/02/19 OpenAI, AI threats, and norm-building for responsible (data) science
18/02/19 ARIMA Model – Complete Guide to Time Series Forecasting in Python
18/02/19 MPhil-PhD transfer seminar – Charitos Charitou
18/02/19 6 concepts of Andrew NG’s book: “Machine Learning Yearning”
18/02/19 #53 Data Science, Gambling and Bookmaking
18/02/19 K Nearest Neighbors
17/02/19 k-nearest neighbor algorithm for supervised learning in Python
17/02/19 Aligning the first line of a triple-quoted string in Python
15/02/19 Predicting sequence from structure
15/02/19 Real World Real Time and Five Papers for Mike Tipping
14/02/19 Better Language Models and Their Implications
13/02/19 Time Series Analysis in Python – A Comprehensive Guide with Examples
13/02/19 AI Has Americans Worried
13/02/19 ML seminar, Wed 20 Feb, 2pm
12/02/19 Local rocks can yield more crops
11/02/19 Creating new spaces for art
11/02/19 Introducing Ludwig, a Code-Free Deep Learning Toolbox
11/02/19 Pachyderm: Data Pipelines with Joe Doliner
11/02/19 #52 Data Science at the BBC
11/02/19 Not every deep learning paper is great. Is that a problem?
08/02/19 Letter regarding the MIT Schwarzman College of Computing working groups and Idea Bank
06/02/19 Peering under the hood of fake-news detectors
05/02/19 TensorFlow — The Scope of Software Engineering
05/02/19 Protect Privacy
05/02/19 How to Increase Retention and Revenue in 1,000 Nontrivial Steps
04/02/19 The Chartis and Forbes Double
04/02/19 3 Questions: Ken Urban on theater, science, and tech
04/02/19 #51 Inclusivity and Data Science
04/02/19 The assumptions of ordinary least squares
01/02/19 The Bezos Paradox and Machine Learning Languages
30/01/19 MPhil-PhD transfer seminar – Fatemeh Najibi
30/01/19 Fair Fares? How airlines get away with differential pricing
29/01/19 Learning to teach to speed up learning
28/01/19 Want to squelch fake news? Let the readers take charge
28/01/19 Quantile regression
27/01/19 Drawing Cairo SVG in a Jupyter notebook
27/01/19 Preparing for the Unexpected
26/01/19 Mystery Hunt 2019
25/01/19 Filling the gaps in a patient’s medical data
25/01/19 Julia Lab joins team to speed up drug approval process
24/01/19 Identifying artificial intelligence “blind spots”
24/01/19 A faster, more efficient cryptocurrency
23/01/19 Do you need machine learning? Maybe. Maybe Not.
22/01/19 Matplotlib Tutorial – A Complete Guide to Python Plot w/ Examples
22/01/19 Price Discrimination in Retail
21/01/19 Think your Data Different
21/01/19 Heterogeneous Treatment Effects
19/01/19 Python Counters @PyDiff
18/01/19 AI, the law, and our future
18/01/19 MIT Press to co-publish new open-access Quantitative Science Studies journal
18/01/19 Democratizing artificial intelligence in health care
18/01/19 Being Global Bit by Bit
15/01/19 The Data Mining Trap
15/01/19 Democratizing data science
15/01/19 Proxy Variables
14/01/19 Manifold: A Model-Agnostic Visual Debugging Tool for Machine Learning at Uber
14/01/19 Contextual Parameter Generation for Neural Machine Translation
14/01/19 Data Visualization using Python
14/01/19 Pre-training language models for natural language processing problems
09/01/19 The Baruch Distinguished Mathematics Lecture Series
09/01/19 MIT adds computational Earth, atmospheric, and planetary sciences to its PhD offerings
09/01/19 School of Engineering welcomes new faculty
08/01/19 Winning Accenture’s HealthTech Challenge – How We Did It
08/01/19 re:Invent in Review: Adrian Cockcroft, Abby Fuller, and Deepak Singh Discuss AWS
08/01/19 Train Transparently
07/01/19 Hackers beware: Bootstrap sampling may be harmful
07/01/19 This one skill will make you a data science rockstar
07/01/19 Facial recognition, society, and the law
04/01/19 On PAC Analysis and Deep Neural Networks
03/01/19 Data Mining – A Cautionary Tale
12/18 How to Build Your Personal Brand as a Data Scientist
12/18 Re-release: Word2Vec
12/18 State Machines and the Strange Case of Mutating API
12/18 The most practical causal inference book I’ve read (is still a draft)
12/18 Re-release: The Cold Start Problem
12/18 Indico 2018 Year in Review
12/18 A thing I learned about Python recursion
12/18 OpenAI Fellows Summer Class of '18: Final Projects
12/18 Heavy Tailed Self Regularization in Deep Neural Nets: 1 year of research
12/18 Equivalence of State Machines and Coroutines
12/18 Convex (and non-convex) optimization
12/18 The Story of a Bad Train-Test Split
12/18 NeurIPS 2018 and End-of-Year ML party
12/18 Research Visit
12/18 A Pretty Good Month
12/18 How AI Training Scales
12/18 Open Source at Uber: Meet Alex Sergeev, Horovod Project Lead
12/18 Massively Parallel Hyperparameter Optimization
12/18 Introducing the ML@CMU Blog
12/18 MIT Sloan launches sports analytics podcast
12/18 TensorFlow Filesystem - Access Tensors Differently
12/18 How Does setState Know What to Do?
12/18 The privacy risks of compiling mobility data
12/18 Quantifying Generalization in Reinforcement Learning
12/18 Topic modeling visualization – How to present the results of LDA models?
12/18 The search for biologically plausible neural computation: A similarity-based approach
12/18 Relationships, Geometry, and Artificial Intelligence
12/18 Optimizing Siri on HomePod in Far‑Field Settings
12/18 The Accenture HealthTech Innovation Challenge and the $812B Opportunity
11/18 A Closer Look at Deep Policy Gradients (Part 2: Gradients and Values)
11/18 A Closer Look at Deep Policy Gradients (Part 1: Intro)
11/18 How to Get a Better GAN (Almost) for Free: Introducing the Metropolis-Hastings GAN
11/18 The Possibility Of Explanation and The End of Season Four
11/18 Apple at NeurIPS 2018
11/18 Top 50 matplotlib Visualizations – The Master Plots (with full python code)
11/18 Quick Opinions on Go-Explore
11/18 #50 Weapons of Math Destruction
11/18 Collaboration at Scale: Highlights from Uber Open Summit 2018
11/18 Introducing pipe, The Automattic Machine Learning Pipeline
11/18 Sixteen grad students named to the Siebel Scholars class of 2019
11/18 Explaining the plummeting cost of solar power
11/18 #49 Data Science Tool Building
11/18 Don’t Peek part 2: Predictions without Test Data
11/18 List Comprehensions in Python – My Simplified Guide
11/18 Machine Learning and AI for the Lean Start Up
11/18 Neural Information Processing Systems and Distributed Internal Intelligence Systems
11/18 Artificial intelligence summit addresses impact of technology on jobs and global economy
11/18 Experience in AI: Uber Hires Jan Pedersen
11/18 NVIDIA: Accelerating Deep Learning with Uber’s Horovod
11/18 GIS and Data Lab now open in Rotch Library
11/18 NimbleText is now a Machine Learning Platform
11/18 #48 Managing Data Science Teams
11/18 Variational Autoencoders Explained in Detail
11/18 Stories From the Neopets Economy
11/18 Bridge to the future of engineering
11/18 The many interfaces of computing
11/18 Understanding optimization in deep learning by analyzing trajectories of gradient descent
11/18 Study: There’s real skill in fantasy sports
11/18 Machine-learning system could aid critical decisions in sepsis care
11/18 Why Prediction Needs Unsupervised Learning
11/18 Why some Wikipedia disputes go unresolved
11/18 Reflections on remote data science work
11/18 Office of Sustainability names 2018 grant winners
11/18 Talk: How Do We Support Under-represented Groups To Put Themselves Forward?
11/18 Study: Impact of mercury-controlling policies shrinks with every five-year delay
11/18 Data Driven Ideas and Actionable Privacy
10/18 The Winds of Change at ACAMS 2018
10/18 Machines that learn language more like kids do
10/18 Model paves way for faster, more efficient translations of more languages
10/18 MassTLC Enterprise AI Workshop: Getting to AI ROI
10/18 Enterprise AI and the Paradox of Accuracy
10/18 #46 AI in Healthcare, an Insider's Account
10/18 How to Engineer Your Way Out of Slow Models
10/18 Apple at EMNLP 2018
10/18 How AI Transforms Business – A New Microsoft Series
10/18 How Can Autonomous Drones Help the Energy and Utilities Industry?
10/18 Michelangelo PyML: Introducing Uber’s Platform for Rapid Python ML Model Development
10/18 Applying Customer Feedback: How NLP & Deep Learning Improve Uber’s Maps
10/18 #45 Decision Intelligence and Data Science
10/18 AI in Regulated Industries: The No-Nonsense Guide
10/18 AI for Good and The Real World
10/18 Machine Reading at Scale – Transfer Learning for Large Text Corpuses
10/18 Machine Learning Trick of the Day (8): Instrumental Thinking
10/18 #44 Project Jupyter and Interactive Computing
10/18 The Most Important Machine Learning Books
10/18 EurAI Advanced Course on AI, 27-31 Aug 2018
10/18 Power Bat – How Spektacom is Powering the Game of Cricket with Microsoft AI
10/18 Decolonising Artificial Intelligence
10/18 Small Data for Big Problems: Practical Transfer Learning for NLP
10/18 Zooming Past the Competition
10/18 How to Learn to Program
10/18 Don’t Peek: Deep Learning without looking … at test data
10/18 #43 Election Forecasting and Polling
10/18 Glossary of Machine Learning Terms
10/18 Mathematical Energy: Etymology
10/18 Deep Learning Without Labels
10/18 “Snip Insights” – An Open Source Cross-Platform AI Tool for Intelligent Screen Capture
10/18 Recommended IDE for Data Scientists and Machine Learning Engineers
10/18 #42 Full Stack Data Science
09/18 Improving Driver Communication through One-Click Chat, Uber’s Smart Reply System
09/18 Can Global Semantic Context Improve Neural Language Models?
09/18 Can AI Generate Programs to Help Automate Busy Work?
09/18 The Price of Transformation
09/18 Should a machine learning beginner go straight for deep learning?
09/18 #41 Uncertainty in Data Science
09/18 This New [AI] Software Constantly Improves – and that Makes all the Difference
09/18 Rank Collapse in Deep Learning
09/18 AI-Based Virtual Tutors – The Future of Education?
09/18 How to Implement AI-First Business Models at Scale
09/18 Introducing Petastorm: Uber ATG’s Data Access Library for Deep Learning
09/18 How to Research in Hype and CIFAR's Strategy
09/18 The Most Important Skills for a Data Scientist
09/18 Simple and efficient semantic embeddings for rare words, n-grams, and language features
09/18 #40 Becoming a Data Scientist
09/18 Monotonicity constraints in machine learning
09/18 Power Laws in Deep Learning 2: Universality
09/18 Variational Autoencoders Explained
09/18 How to Get Your First Data Science Job
09/18 Food Discovery with Uber Eats: Recommending for the Marketplace
09/18 Power Laws in Deep Learning
09/18 #39 Data Science at Stitch Fix
09/18 A Brief History of ASR: Automatic Speech Recognition
09/18 Troubling Trends and Climbing Mountains
09/18 Forecasting at Uber: An Introduction
09/18 Connectionist Temporal Classification
09/18 #38 Data Products, Dashboards and Rapid Prototyping
09/18 The Most Important Machine Learning Algorithms
08/18 Clustering: a draft of a part!
08/18 Data Science Work Productivity Tips & Tricks
08/18 #37 Data Science and Insurance
08/18 Big O Notation, How it Works and What It's Used For
08/18 Agile and Non-Agile Project Management
08/18 What Machine Learning Can Do
08/18 Scaling Uber’s Customer Support Ticket Assistant (COTA) System with Deep Learning
08/18 Gaussian Processes, Grad School, and Richard Zemel
08/18 The State of Artificial Intelligence and Need for Standards: A Conversation with Syed Husain
08/18 Uncertainty for CTR Prediction: One Model to Clarify Them All
08/18 #36 Data Science and Ecology
08/18 Three Years Later
08/18 Motivating the rules of the game for adversarial example research
08/18 Distill Update 2018
08/18 Recommender Systems: Exploring the Unknown Using Uncertainty
08/18 How Do Machines Learn
08/18 #35 Data Science in Finance
08/18 Bitcoin and Blockchain books, videos and learning resources
08/18 Training Robust Classifiers (Part 2)
08/18 Long Term Fairness
08/18 Finding Local Destinations with Siri’s Regionally Specific Language Models for Speech Recognition
08/18 Neural Networks from a Bayesian Perspective
08/18 Five Seconds to Midnight
08/18 #34 Data Journalism & Interactive Visualization
07/18 Using Uncertainty to Interpret your Model
07/18 ArchiMate® Modeling Language and Agile – A Conversation with Marc Lankhorst
07/18 #33 Pharmaceuticals and Data Science
07/18 When Recurrent Models Don't Need to be Recurrent
07/18 Simulated Learning and Real World Ethics
07/18 Differentiable Image Parameterizations
07/18 Introduction to NLP
07/18 Minkowski's, Dirichlet's, and Two Squares Theorem
07/18 Reduced Betti number of sphere: Mayer-Vietoris Theorem
07/18 #32 Data Science at Doctors without Borders
07/18 Defining data science in 2018
07/18 Python real-time plotting
07/18 ArchiMate® Standard and Other Modeling Notations – A Conversation with Marc Lankhorst
07/18 ETL vs ELT: Considering the Advancement of Data Warehouses
07/18 Brouwer's Fixed Point Theorem: A Proof with Reduced Homology
07/18 Neural Networks gone wild! They can sample from discrete distributions now!
07/18 #31 Chatbots, Conversational Software & Data Science
07/18 ICML 2018 with Jennifer Dy
07/18 Training Robust Classifiers (Part 1)
07/18 An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution
07/18 Feature-wise transformations
07/18 #30 Data Science at McKinsey
07/18 Transforming Financial Forecasting with Data Science and Machine Learning at Uber
07/18 #29 Machine Learning & Data Science at Github
06/18 Aspirational Asimov and How to Survive a Conference
06/18 Quick Opinions on OpenAI Five
06/18 Deep-learning-free Text and Sentence Embedding, Part 2
06/18 #28 Organizing Data Science Teams
06/18 An Outsider's Tour of Reinforcement Learning
06/18 Conceptual issues in AI safety: the paradigmatic gap
06/18 Deep Learning: Theory & Practice
06/18 #27 Data Security, Data Privacy and the GDPR
06/18 Deep-learning-free Text and Sentence Embedding, Part 1
06/18 How Trip Inferences and Machine Learning Optimize Delivery Times on Uber Eats
06/18 The Hitchhiker's Guide to Hyperparameter Tuning
06/18 Explanations and Reviews
06/18 Advanced Technologies for Detecting and Preventing Fraud at Uber
06/18 #26 Spreadsheets in Data Science
06/18 The Math Art of Gábor Damásdi
06/18 Thoughts On ICLR 2018 and ICRA 2018
06/18 Self-Regularization in Deep Neural Networks: a preview
06/18 Going Global: Highlights from the Second Annual Uber Technology Day
06/18 #25 Data Science for Everyone
05/18 Statements on Statements
05/18 #23 Online Experiments at Booking.com
05/18 The Futility of Artificial Carpenters and Further Reading
05/18 #22 Robust Data Science with Statistical Modeling
05/18 #21 The Fight Against Cancer
05/18 Economies, Work and AI
04/18 #20 Kaggle and the Future of Data Science
04/18 Creating a dict of lists in Python
04/18 Measuring the Intrinsic Dimension of Objective Landscapes
04/18 Accelerating Deep Neuroevolution: Train Atari in Hours on a Single Personal Computer
04/18 The Logistic Regression Algorithm
04/18 #19 Automated Machine Learning
04/18 Explainability and the Inexplicable
04/18 The Best Things in Life Are Model Free
04/18 Mediation Modeling at Uber: Understanding Why Product Changes Work (and Don’t Work)
04/18 The Batch Normalization layer of Keras is broken
04/18 Personalized Hey Siri
04/18 Transfer Learning
04/18 #18 Deep Learning at NVIDIA
04/18 Do brains represent words?
04/18 Differentiable Plasticity: A New Method for Learning to Learn
04/18 Pros and Cons of Neural Networks
04/18 #17 Biology and Deep Learning
04/18 Word morphing
04/18 Good Data Practice Rules
04/18 Evaluation Metrics for Classification
04/18 #16 Data Nerdism at Large
03/18 This is not an academic post
03/18 #15 Building Data Science Teams
03/18 Benchmarking Machine Learning with Performance Profiles
03/18 How to build a Neural Network with Keras
03/18 Gated Multimodal Units for Information Fusion
03/18 Can an AI Practitioner Fix a Radio?
03/18 Engineering Data Science at Automattic
03/18 Lessons learned at USDS
03/18 #14 Text Mining and Natural Language Processing in Data Science
03/18 VINE: An Open Source Interactive Data Visualization Tool for Neuroevolution
03/18 Natural Gradient Descent
03/18 I saw a dog
03/18 #13 Fake News Detection with Data Science
03/18 Fisher Information Matrix
03/18 Center for Algorithms and Machine Learning
03/18 Natural vs Artificial Intelligence and Doing Unexpected Work
03/18 Optimizing Learned Bloom Filters with Sandwiching
03/18 The Building Blocks of Interpretability
03/18 #12 Data Science, Nuclear Engineering and the Open Source
03/18 Postdoc at the Center for Algorithms and Machine Learning
03/18 Can increasing depth serve to accelerate optimization?
02/18 #11 Data Science at BuzzFeed and the Digital Media Landscape
02/18 Scientific Rigor and Turning Information into Action
02/18 #10 Data Science, the Environment and MOOCs
02/18 Proving generalization of deep nets via compression
02/18 #9 Data Science and Online Experiments at Etsy
02/18 Code Review for Community Change
02/18 #8 Data Science, Astronomy and the Open Source
01/18 #7 Data Science at Airbnb
01/18 What's New in the Big Data Theory 2017
01/18 Some Notes on "Learned Bloom Filters"
01/18 5 tips for multi-GPU training with Keras
01/18 #2 How Data Science is Impacting Telecommunications Networks
01/18 #3 How Data Science and Machine Learning are Shaping Digital Advertising
01/18 #4 How Data Science is Revolutionizing the Trucking Industry
01/18 #5 Data Science, Epidemiology and Public Health
01/18 #6 Citizen Data Science
01/18 #1 Data Science, Past, Present and Future
01/18 #0 Introducing DataFramed
01/18 Machine Learning Trick of the Day (7): Density Ratio Trick
01/18 The State of VACUUM
12/17 Introduction to Annealed Importance Sampling
12/17 Adaptive Data Analysis Class Notes
12/17 k-server, part 1: online learning and online algorithms
12/17 Learning with Privacy at Scale
12/17 Using Artificial Intelligence to Augment Human Intelligence
11/17 Sequence Modeling with CTC
11/17 Positions in eg. Data Intelligence/UBC/CA
11/17 An On-device Deep Neural Network for Face Detection
11/17 Between "statistical" and "individual" notions of fairness in Machine Learning
11/17 Algorithms, Machine Learning, and Optimization: we are hiring!
11/17 Feature Visualization
10/17 Introducing EulerCoin, a new cryptocurrency for Mathematicians, Educators and Learners
10/17 Advice for aspiring data scientists and other FAQs
10/17 Considering Python's Target Audience
10/17 Ubuntu 17.10: a last minute review
10/17 The Pace of Change and The Public View of ML
10/17 Hey Siri: An On-device DNN-powered Voice Trigger for Apple’s Personal Assistant
09/17 On music, mathematics and teaching.
09/17 The Long View and Learning in Person
09/17 How to prepare for a Vipassana retreat
09/17 Machine Learning in the Field and Bayesian Baked Goods
09/17 Gibbs Sampler for LDA
08/17 Datumbox Machine Learning Framework v0.8.1 released
08/17 Data Science and Social Good
08/17 Data Science Africa with Dina Machuve
07/17 My 10-step path to becoming a remote data scientist with Automattic
07/17 The Church of Bayes and Collecting Data
07/17 A Math Loss
07/17 Getting a Start in ML and Applied AI at Facebook
06/17 Bias Variance Dilemma for Humans and the Arm Farm
06/17 Overfitting and Asking Ecological Questions with ML
06/17 The water is rising, we must learn to swim…
06/17 Exploring and visualising reef life survey data
05/17 Graphons and "Inferencing"
05/17 Slicing a list evenly with Python
04/17 Hosts of Talking Machines: Neil Lawrence and Ryan Adams
04/17 Data Science and Game Theory Workshop
04/17 Why Momentum Really Works
03/17 From bytes to strings in Python and back again
03/17 Research Debt
03/17 Cognitive Machine Learning (2): Uncertain Thoughts
03/17 Boundary Seeking GAN
02/17 Sunday links
02/17 Drilling into Spark’s ALS Recommendation algorithm
02/17 Bridging principles
02/17 Next Generation, Artificial Intelligence and Machine Learning
02/17 Mission Critical Artificial Intelligence for Real-Time Fraud Prevention
02/17 Same-Day ACH Fraud Prevention with Artificial Intelligence & Machine Learning
02/17 AI, Machine Learning, & The Future of Personalization
02/17 Cognitive Machine Learning (1): Learning to Explain
01/17 Deep Learning/ Neural Networks
01/17 Data Mining
01/17 Datumbox Machine Learning Framework version 0.8.0 released
12/16 What's New in the Big Data Theory 2016
12/16 Experiments in Handwriting with a Neural Network
12/16 Linear regression in the wild
11/16 How to learn English Vocabulary efficiently
11/16 Location History Analysis
11/16 Avoid committing junk
11/16 Pelican and GitHub Pages workflow
10/16 Random forest interpretation – conditional feature contributions
10/16 Detecting Anomalies in a SMART Way (Part Three)
10/16 Deconvolution and Checkerboard Artifacts
10/16 How to Use t-SNE Effectively
10/16 Gradient descent learns linear dynamical systems
10/16 Cognitive Machine Learning: Prologue
10/16 Situated language learning
09/16 Detecting Anomalies in a SMART Way (Part Two)
09/16 My two-lecture intro to Analysis of Boolean Functions, at St. Petersburg State University
09/16 Sunday Links
09/16 The Python Packaging Ecosystem
09/16 Detecting Anomalies in a SMART Way
09/16 Who wants to be a coder
09/16 Attention and Augmented Recurrent Neural Networks
09/16 Approaching fairness in machine learning
09/16 ANGLICAN and Probabilistic Programming
08/16 Teaching Foundations of Data Science
08/16 Adaptive Data Analysis Workshop
08/16 Call for Papers: Second Workshop on Adaptive Data Analysis
08/16 Eric Lander and Restricted Boltzmann Machines
08/16 On "solving language"
08/16 Generative Art and Hamiltonian Monte Carlo
07/16 Talk: Building Machines that Imagine and Reason
07/16 Learning in Brains and Machines (4): Episodic and Interactive Memory
07/16 Perturb-and-MAP and Machine Learning in the Flint Water Crisis
07/16 Automatic Translation and t-SNE
06/16 Hybrid tree-sequence neural networks with SPINN
06/16 Fantasizing Cats and Data Numbers
06/16 Life update
06/16 Machine Learning Postdoc
06/16 Spark and ICML
05/16 Neural networks in Kotlin (part 2)
05/16 Neural Network in Kotlin
05/16 Fairness in Learning
05/16 Computational Learning Theory and Machine Learning for Understanding Cells
05/16 Sparse Coding and MADBITS
04/16 Remembering David MacKay
04/16 Machine Learning and Society
03/16 Software and Statistics for Machine Learning
03/16 Datumbox Machine Learning Framework 0.7.0 Released
03/16 Stability as a foundation of machine learning
03/16 Machine Learning in Healthcare and The AlphaGo Matches
02/16 Histogram intersection for change detection
02/16 AI Safety and The Legacy of Bletchley Park
02/16 Robotics and Machine Learning Music Videos
01/16 OpenAI and Gaussian Processes
01/16 The Simple Economics of Algorithms for Big Data
01/16 Real Human Actions and Women in Machine Learning
01/16 Datumbox Machine Learning Framework 0.6.1 Released
12/15 Teaching algorithms for Big Data
12/15 Who are the best MMA fighters of all time. A Bayesian study
12/15 Adaptive data analysis
11/15 First Estonian Machine Learning Meetup
11/15 Open Source Releases and The End of Season One
11/15 Probabilistic Programming and Digital Humanities
10/15 Workshops at NIPS and Crowdsourcing in Machine Learning
10/15 7 tools in every data scientist’s toolbox
10/15 27 languages to improve your Python
10/15 Machine Learning Mastery and Cancer Clusters
09/15 Data from Video Games and The Master Algorithm
09/15 Strong AI and Autoencoders
08/15 Active Learning and Machine Learning in Neuroscience
08/15 algorithms for Big Data
08/15 Machine Learning in Biology and Getting into Grad School
08/15 Random forest interpretation with scikit-learn
07/15 Machine Learning for Sports and Real Time Predictions
07/15 Really Really Big Data and Machine Learning in Business
07/15 TCP echo client and server in Python 3.5
07/15 Background tasks in Python 3.5
07/15 Solving Intelligence and Machine Learning Fundamentals
06/15 Working With Data and Machine Learning in Advertising
06/15 The Economic Impact of Machine Learning and Using The Kernel Trick on Big Data
06/15 Prediction intervals for Random Forests
05/15 How We Think About Privacy and Finding Features in Black Boxes
05/15 Interdisciplinary Data and Helping Humans Be Creative
05/15 Datumbox Machine Learning Framework 0.6.0 Released
04/15 Starting Simple and Machine Learning in Meds
04/15 Algorithmic Game Theory and Data Science
04/15 Spinning Programming Plates and Creative Algorithms
03/15 The Automatic Statistician and Electrified Meat
03/15 Conditional generative adversarial networks for face generation
03/15 The Big Workshop on Big Data
03/15 The Future of Machine Learning from the Inside Out
03/15 Competing in a data science contest without reading the data
02/15 The History of Machine Learning from the Inside Out
02/15 Which topics get the upvote on Hacker News?
02/15 Using Models in the Wild and Women in Machine Learning
01/15 Common Sense Problems and Learning about Machine Learning
01/15 Machine Learning and Magical Thinking
01/15 Machine learning and technical debt
01/15 Hello World!
12/14 Selecting good features – Part IV: stability selection, RFE and everything side by side
11/14 How to install and use the Datumbox Machine Learning Framework
10/14 New open-source Machine Learning Framework written in Java
09/14 How big data is unfair
09/14 A GloVe implementation in Python
09/14 Summarizing Spanish with Stanford CoreNLP
09/14 Nesin Mathematics Village and Swedish Summer School
08/14 On Metacademy and knowledge graphs
07/14 Where does ice cream come from?
07/14 Clustering with Dirichlet Process Mixture Model in Java
07/14 An Encore: More Learning and Testing – STOC 2014 Recaps (Part 8)
06/14 Clustering documents and gaussian data with Dirichlet Process Mixture Models
06/14 The Dirichlet Process Mixture Model
05/14 The Dirichlet Process the Chinese Restaurant Process and other representations
05/14 Finite Mixture Model based on Dirichlet Distribution
05/14 Overview of Cluster Analysis and Dirichlet Process Mixture Models
04/14 Using Artificial Intelligence to solve the 2048 Game (JAVA code)
03/14 Measuring the Social Media Popularity of Pages with DEA in JAVA
02/14 Data Envelopment Analysis Tutorial
02/14 How to build your own Facebook Sentiment Analysis Tool
01/14 Developing a Naive Bayes Text Classifier in JAVA
01/14 Using Feature Selection Methods in Text Classification
01/14 Permanent bans to duplicate account owners
01/14 Kneser-Ney smoothing explained
12/13 The wacky economics of gift-giving
12/13 Imperat aut servit: Managing our knowledge inheritance
11/13 Machine Learning Tutorial: The Multinomial Logistic Regression (Softmax Regression)
11/13 Machine Learning Tutorial: The Max Entropy Text Classifier
11/13 Marcus Aurelius and slavery in the Roman Empire
10/13 Book review: Introduction to Computer Science Using Python (by Charles Dierbach)
10/13 Tuning the learning rate in Gradient Descent
10/13 Coding Brain Neurons by using Hodgkin-Huxley model
06/13 Review: ZeroMQ: Messaging for Many Applications by Pieter Hintjens
04/13 Review: Clojure Programming by Chas Emerick et al.
12/12 Parsing sound change rules with Parsec: Part 2
12/12 Parsing sound change rules with Parsec: Part 1
08/12 Hillis β-reduction in Haskell
07/12 Data Streaming in Dortmund: Day 3
07/12 Data Streaming in Dortmund: Day 1
07/12 Hillis beta reduction improvements
07/12 Hillis beta reduction in Clojure
07/12 Disabling electric indenting in Emacs modes
02/12 Postdocs in data privacy at Penn State
01/12 Post excerpts in Jekyll
11/11 Another algorithms person at Oregon State? It could be *you*!
07/11 Before Python
06/11 The depth and breadth of Python
01/11 A new App Engine datastore API
11/09 Python in the Scientific World
09/09 Lovely Python!
06/09 IronPython in Action and the Decline of Windows
05/09 So you want to learn Python?
05/09 Hadoop Sorts a Petabyte
03/09 SOA Funding Models