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 TR19-060 | Gentle Measurement of Quantum States and Differential Privacy | Scott Aaronson, Guy Rothblum

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 A Continuous-Time View of Early Stopping for Least Squares (or: How I Learned to Stop Worrying and Love Early Stopping)

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 President Reif calls for federal funding, focused education to address “opportunity and threat” of AI

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 Should we remove duplicates from a data-set while training a Machine Learning algorithm (shallow and/or deep methods)?

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 POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer

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 My Journey from Working as a Fabric Weaver in Ethiopia to Becoming a Software Engineer at Uber in San Francisco

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

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 Brighterion Closes Out 2017 With Two Prestigious Awards in the Field of Artificial Intelligence and Machine Learning

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 Real-Time Recognition of Handwritten Chinese Characters Spanning a Large Inventory of 30,000 Characters

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 Next generation anti-money laundering and compliance powered by business rules, artificial intelligence and machine learning

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

07/07 MapReduce cookbook for machine learning

Last update: Thu May 02 21:39:03 CEST 2019