| Title |
Duration
| Published |
Consumed |
|
So long, and thanks for all the fish
|
00:35:44 |
2020-07-27 01:32
|
|
|
A Reality Check on AI-Driven Medical Assistants
|
00:14:00 |
2020-07-20 01:51
|
|
|
A Data Science Take on Open Policing Data
|
00:23:44 |
2020-07-13 04:02
|
|
|
Procella: YouTube's super-system for analytics data storage
|
00:29:48 |
2020-07-06 04:29
|
|
|
The Data Science Open Source Ecosystem
|
00:23:06 |
2020-06-29 04:34
|
|
|
Rock the ROC Curve
|
00:15:52 |
2020-06-22 01:34
|
|
|
Criminology and Data Science
|
00:30:57 |
2020-06-15 03:26
|
|
|
Racism, the criminal justice system, and data science
|
00:31:36 |
2020-06-08 01:33
|
|
|
An interstitial word from Ben
|
00:05:59 |
2020-06-05 03:38
|
|
|
Convolutional Neural Networks
|
00:21:55 |
2020-05-31 23:46
|
|
|
Stein's Paradox
|
00:27:02 |
2020-05-25 00:21
|
|
|
Protecting Individual-Level Census Data with Differential Privacy
|
00:21:19 |
2020-05-18 03:49
|
|
|
Causal Trees
|
00:15:27 |
2020-05-11 03:34
|
|
|
The Grammar Of Graphics
|
00:35:38 |
2020-05-04 03:12
|
|
|
Gaussian Processes
|
00:20:55 |
2020-04-27 03:33
|
|
|
Keeping ourselves honest when we work with observational healthcare data
|
00:19:08 |
2020-04-20 04:43
|
|
|
Changing our formulation of AI to avoid runaway risks: Interview with Prof. Stuart Russell
|
00:28:58 |
2020-04-13 03:55
|
|
|
Putting machine learning into a database
|
00:24:22 |
2020-04-06 03:51
|
|
|
The work-from-home episode
|
00:29:06 |
2020-03-30 00:23
|
|
|
Understanding Covid-19 transmission: what the data suggests about how the disease spreads
|
00:25:25 |
2020-03-23 02:03
|
|
|
Network effects re-release: when the power of a public health measure lies in widespread adoption
|
00:26:40 |
2020-03-15 23:43
|
|
|
Causal inference when you can't experiment: difference-in-differences and synthetic controls
|
00:20:48 |
2020-03-09 02:39
|
|
|
Better know a distribution: the Poisson distribution
|
00:31:51 |
2020-03-02 03:55
|
|
|
The Lottery Ticket Hypothesis
|
00:19:45 |
2020-02-24 00:03
|
|
|
Interesting technical issues prompted by GDPR and data privacy concerns
|
00:20:26 |
2020-02-17 02:50
|
|
|
Thinking of data science initiatives as innovation initiatives
|
00:17:27 |
2020-02-10 02:10
|
|
|
Building a curriculum for educating data scientists: Interview with Prof. Xiao-Li Meng
|
00:31:36 |
2020-02-03 00:36
|
|
|
Running experiments when there are network effects
|
00:24:45 |
2020-01-27 01:13
|
|
|
Zeroing in on what makes adversarial examples possible
|
00:22:51 |
2020-01-20 03:41
|
|
|
Unsupervised Dimensionality Reduction: UMAP vs t-SNE
|
00:29:34 |
2020-01-13 01:53
|
|
|
Data scientists: beware of simple metrics
|
00:24:47 |
2020-01-05 23:54
|
|
|
Communicating data science, from academia to industry
|
00:26:15 |
2019-12-30 02:53
|
|
|
Optimizing for the short-term vs. the long-term
|
00:19:24 |
2019-12-23 03:50
|
|
|
Interview with Prof. Andrew Lo, on using data science to inform complex business decisions
|
00:27:46 |
2019-12-16 04:15
|
|
|
Using machine learning to predict drug approvals
|
00:25:00 |
2019-12-08 23:56
|
|
|
Facial recognition, society, and the law
|
00:43:09 |
2019-12-02 04:14
|
|
|
Lessons learned from doing data science, at scale, in industry
|
00:28:00 |
2019-11-25 01:45
|
|
|
Varsity A/B Testing
|
00:36:00 |
2019-11-18 03:09
|
|
|
The Care and Feeding of Data Scientists: Growing Careers
|
00:25:19 |
2019-11-11 04:44
|
|
|
The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists
|
00:20:16 |
2019-11-04 01:21
|
|
|
The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists
|
00:20:16 |
2019-11-04 01:19
|
|
|
The Care and Feeding of Data Scientists: Becoming a Data Science Manager
|
00:24:45 |
2019-10-28 02:27
|
|
|
Procella: YouTube's super-system for analytics data storage
|
00:29:48 |
2019-10-21 03:27
|
|
|
Kalman Runners
|
00:15:59 |
2019-10-13 22:04
|
|
|
What's *really* so hard about feature engineering?
|
00:21:18 |
2019-10-07 00:37
|
|
|
Data storage for analytics: stars and snowflakes
|
00:15:22 |
2019-09-30 13:22
|
|
|
Data storage: transactions vs. analytics
|
00:16:08 |
2019-09-23 03:49
|
|
|
GROVER: an algorithm for making, and detecting, fake news
|
00:18:28 |
2019-09-16 05:21
|
|
|
Data science teams as innovation initiatives
|
00:15:21 |
2019-09-09 04:24
|
|
|
Can Fancy Running Shoes Cause You To Run Faster?
|
00:30:15 |
2019-09-02 01:44
|
|
|
Organizational Models for Data Scientists
|
00:23:09 |
2019-08-26 01:06
|
|
|
Data Shapley
|
00:16:55 |
2019-08-19 04:38
|
|
|
A Technical Deep Dive on Stanley, the First Self-Driving Car
|
00:41:32 |
2019-08-12 04:21
|
|
|
An Introduction to Stanley, the First Self-Driving Car
|
00:14:19 |
2019-08-05 02:28
|
|
|
Putting the "science" in data science: the scientific method, the null hypothesis, and p-hacking
|
00:24:11 |
2019-07-29 03:30
|
|
|
Interleaving
|
00:16:54 |
2019-07-22 14:20
|
|
|
Federated Learning
|
00:15:03 |
2019-07-15 01:00
|
|
|
Endogenous Variables and Measuring Protest Effectiveness
|
00:17:58 |
2019-07-08 00:59
|
|
|
Deepfakes
|
00:15:08 |
2019-07-01 03:25
|
|
|
Revisiting Biased Word Embeddings
|
00:18:09 |
2019-06-24 02:26
|
|
|
Attention in Neural Nets
|
00:26:32 |
2019-06-17 02:28
|
|
|
Interview with Joel Grus
|
00:39:46 |
2019-06-10 04:05
|
|
|
Re - Release: Factorization Machines
|
00:20:09 |
2019-06-03 03:32
|
|
|
Re-release: Auto-generating websites with deep learning
|
00:19:38 |
2019-05-27 04:01
|
|
|
Advice to those trying to get a first job in data science
|
00:17:33 |
2019-05-19 23:50
|
|
|
Re - Release: Machine Learning Technical Debt
|
00:22:29 |
2019-05-13 01:07
|
|
|
Estimating Software Projects, and Why It's Hard
|
00:19:07 |
2019-05-06 00:27
|
|
|
The Black Hole Algorithm
|
00:20:17 |
2019-04-29 02:55
|
|
|
Structure in AI
|
00:19:05 |
2019-04-22 00:29
|
|
|
The Great Data Science Specialist vs. Generalist Debate
|
00:14:10 |
2019-04-15 02:55
|
|
|
Google X, and Taking Risks the Smart Way
|
00:19:04 |
2019-04-08 03:10
|
|
|
Statistical Significance in Hypothesis Testing
|
00:22:34 |
2019-04-01 03:34
|
|
|
The Language Model Too Dangerous to Release
|
00:21:01 |
2019-03-25 02:39
|
|
|
The cathedral and the bazaar
|
00:32:36 |
2019-03-17 23:47
|
|
|
AlphaStar
|
00:22:03 |
2019-03-11 02:18
|
|
|
Are machine learning engineers the new data scientists?
|
00:20:46 |
2019-03-04 03:57
|
|
|
Interview with Alex Radovic, particle physicist turned machine learning researcher
|
00:35:42 |
2019-02-25 02:59
|
|
|
K Nearest Neighbors
|
00:16:25 |
2019-02-18 00:57
|
|
|
Not every deep learning paper is great. Is that a problem?
|
00:17:54 |
2019-02-11 01:06
|
|
|
The Assumptions of Ordinary Least Squares
|
00:25:07 |
2019-02-04 00:24
|
|
|
Quantile Regression
|
00:21:46 |
2019-01-28 02:27
|
|
|
Heterogeneous Treatment Effects
|
00:17:24 |
2019-01-21 00:57
|
|
|
Pre-training language models for natural language processing problems
|
00:27:35 |
2019-01-14 01:42
|
|
|
Facial Recognition, Society, and the Law
|
00:42:46 |
2019-01-07 03:03
|
|
|
Re-release: Word2Vec
|
00:17:59 |
2018-12-31 02:56
|
|
|
Re - Release: The Cold Start Problem
|
00:15:37 |
2018-12-23 21:23
|
|
|
Convex (and non-convex) Optimization
|
00:20:00 |
2018-12-17 04:06
|
|
|
The Normal Distribution and the Central Limit Theorem
|
00:27:11 |
2018-12-09 19:58
|
|
|
Software 2.0
|
00:17:22 |
2018-12-03 00:23
|
|
|
Limitations of Deep Nets for Computer Vision
|
00:27:20 |
2018-11-18 20:01
|
|
|
Building Data Science Teams
|
00:25:09 |
2018-11-12 04:16
|
|
|
Optimized Optimized Web Crawling
|
00:19:42 |
2018-11-04 22:38
|
|
|
Optimized Web Crawling
|
00:21:32 |
2018-10-29 00:56
|
|
|
Better Know a Distribution: The Poisson Distribution
|
00:31:51 |
2018-10-22 02:53
|
|
|
Searching for Datasets with Google
|
00:19:54 |
2018-10-15 03:11
|
|
|
It's our fourth birthday
|
00:22:06 |
2018-10-08 04:33
|
|
|
Gigantic Searches in Particle Physics
|
00:24:46 |
2018-09-30 20:52
|
|
|
Gigantic Searches in Particle Physics
|
00:24:46 |
2018-09-30 20:51
|
|
|
Data Engineering
|
00:16:22 |
2018-09-24 03:10
|
|
|
Text Analysis for Guessing the NYTimes Op-Ed Author
|
00:18:37 |
2018-09-16 20:13
|
|
|
The Three Types of Data Scientists, and What They Actually Do
|
00:23:25 |
2018-09-09 21:00
|
|
|
Agile Development for Data Scientists, Part 2: Where Modifications Help
|
00:27:17 |
2018-08-26 21:59
|
|
|
Agile Development for Data Scientists, Part 1: The Good
|
00:25:56 |
2018-08-19 20:06
|
|
|
Re - Release: How To Lose At Kaggle
|
00:17:54 |
2018-08-13 04:31
|
|
|
Troubling Trends In Machine Learning Scholarship
|
00:29:35 |
2018-08-06 03:31
|
|
|
Can Fancy Running Shoes Cause You To Run Faster?
|
00:28:37 |
2018-07-29 21:12
|
|
|
Compliance Bias
|
00:23:28 |
2018-07-22 18:07
|
|
|
AI Winter
|
00:19:02 |
2018-07-15 22:11
|
|
|
Rerelease: How to Find New Things to Learn
|
00:18:32 |
2018-07-09 00:28
|
|
|
Rerelease: Space Codes
|
00:24:30 |
2018-07-02 06:36
|
|
|
Rerelease: Anscombe's Quartet
|
00:16:14 |
2018-06-25 03:20
|
|
|
Rerelease: Hurricanes Produced
|
00:28:12 |
2018-06-18 19:00
|
|
|
GDPR
|
00:18:24 |
2018-06-11 04:24
|
|
|
Git for Data Scientists
|
00:22:05 |
2018-06-03 19:52
|
|
|
Analytics Maturity
|
00:19:32 |
2018-05-20 17:09
|
|
|
SHAP: Shapley Values in Machine Learning
|
00:19:12 |
2018-05-13 16:24
|
|
|
Game Theory for Model Interpretability: Shapley Values
|
00:27:06 |
2018-05-07 04:17
|
|
|
AutoML
|
00:15:24 |
2018-04-30 04:50
|
|
|
CPUs, GPUs, TPUs: Hardware for Deep Learning
|
00:12:40 |
2018-04-23 04:52
|
|
|
A Technical Introduction to Capsule Networks
|
00:31:28 |
2018-04-16 03:12
|
|
|
A Conceptual Introduction to Capsule Networks
|
00:14:05 |
2018-04-09 03:59
|
|
|
Convolutional Neural Nets
|
00:21:55 |
2018-04-02 03:40
|
|
|
Google Flu Trends
|
00:12:46 |
2018-03-26 03:20
|
|
|
How to pick projects for a professional data science team
|
00:31:17 |
2018-03-19 04:07
|
|
|
Autoencoders
|
00:12:41 |
2018-03-12 02:47
|
|
|
When Private Data Isn't Private Anymore
|
00:26:20 |
2018-03-05 04:35
|
|
|
What makes a machine learning algorithm "superhuman"?
|
00:34:48 |
2018-02-26 05:52
|
|
|
Open Data and Open Science
|
00:16:54 |
2018-02-19 02:39
|
|
|
Defining the quality of a machine learning production system
|
00:20:29 |
2018-02-12 03:00
|
|
|
Auto-generating websites with deep learning
|
00:19:24 |
2018-02-05 00:02
|
|
|
The Case for Learned Index Structures, Part 2: Hash Maps and Bloom Filters
|
00:20:41 |
2018-01-29 03:15
|
|
|
The Case for Learned Index Structures, Part 1: B-Trees
|
00:18:50 |
2018-01-22 03:32
|
|
|
Challenges with Using Machine Learning to Classify Chest X-Rays
|
00:18:00 |
2018-01-15 02:57
|
|
|
The Fourier Transform
|
00:15:39 |
2018-01-08 03:07
|
|
|
Statistics of Beer
|
00:15:20 |
2018-01-02 02:57
|
|
|
Re - Release: Random Kanye
|
00:09:33 |
2017-12-24 20:07
|
|
|
Debiasing Word Embeddings
|
00:18:20 |
2017-12-18 03:31
|
|
|
The Kernel Trick and Support Vector Machines
|
00:17:48 |
2017-12-11 02:58
|
|
|
Maximal Margin Classifiers
|
00:14:21 |
2017-12-04 05:03
|
|
|
Re - Release: The Cocktail Party Problem
|
00:13:43 |
2017-11-27 03:11
|
|
|
Clustering with DBSCAN
|
00:16:14 |
2017-11-20 04:08
|
|
|
The Kaggle Survey on Data Science
|
00:25:20 |
2017-11-13 03:49
|
|
|
Machine Learning: The High Interest Credit Card of Technical Debt
|
00:22:18 |
2017-11-06 05:35
|
|
|
Improving Upon a First-Draft Data Science Analysis
|
00:15:01 |
2017-10-30 02:38
|
|
|
Survey Raking
|
00:17:23 |
2017-10-23 04:51
|
|
|
Happy Hacktoberfest
|
00:15:40 |
2017-10-16 03:46
|
|
|
Re - Release: Kalman Runners
|
00:17:53 |
2017-10-09 04:28
|
|
|
Neural Net Dropout
|
00:18:53 |
2017-10-02 05:32
|
|
|
Disciplined Data Science
|
00:29:34 |
2017-09-25 03:49
|
|
|
Hurricane Forecasting
|
00:27:57 |
2017-09-18 03:37
|
|
|
Finding Spy Planes with Machine Learning
|
00:18:09 |
2017-09-11 04:11
|
|
|
Data Provenance
|
00:22:48 |
2017-09-04 03:35
|
|
|
Adversarial Examples
|
00:16:11 |
2017-08-28 04:25
|
|
|
Jupyter Notebooks
|
00:15:50 |
2017-08-21 03:09
|
|
|
Curing Cancer with Machine Learning is Super Hard
|
00:19:20 |
2017-08-14 03:49
|
|
|
KL Divergence
|
00:25:38 |
2017-08-07 05:07
|
|
|
Sabermetrics
|
00:25:48 |
2017-07-31 03:15
|
|
|
What Data Scientists Can Learn from Software Engineers
|
00:23:46 |
2017-07-24 03:52
|
|
|
Software Engineering to Data Science
|
00:19:05 |
2017-07-17 04:36
|
|
|
Re-Release: Fighting Cholera with Data, 1854
|
00:12:04 |
2017-07-10 02:19
|
|
|
Re-Release: Data Mining Enron
|
00:32:16 |
2017-07-02 19:53
|
|
|
Factorization Machines
|
00:19:54 |
2017-06-26 04:23
|
|
|
Anscombe's Quartet
|
00:15:39 |
2017-06-19 04:19
|
|
|
Traffic Metering Algorithms
|
00:18:34 |
2017-06-12 05:01
|
|
|
Page Rank
|
00:19:58 |
2017-06-05 03:46
|
|
|
Fractional Dimensions
|
00:20:28 |
2017-05-29 04:54
|
|
|
Things You Learn When Building Models for Big Data
|
00:21:39 |
2017-05-22 03:44
|
|
|
How to Find New Things to Learn
|
00:17:54 |
2017-05-15 03:49
|
|
|
Federated Learning
|
00:14:03 |
2017-05-08 03:50
|
|
|
Word2Vec
|
00:17:59 |
2017-05-01 04:17
|
|
|
Feature Processing for Text Analytics
|
00:17:28 |
2017-04-24 04:17
|
|
|
Education Analytics
|
00:21:05 |
2017-04-17 04:09
|
|
|
A Technical Deep Dive on Stanley, the First Self-Driving Car
|
00:40:42 |
2017-04-10 03:50
|
|
|
An Introduction to Stanley, the First Self-Driving Car
|
00:13:07 |
2017-04-03 03:34
|
|
|
Feature Importance
|
00:20:15 |
2017-03-27 03:53
|
|
|
Space Codes!
|
00:23:56 |
2017-03-20 03:50
|
|
|
Finding (and Studying) Wikipedia Trolls
|
00:15:50 |
2017-03-13 02:44
|
|
|
A Sprint Through What's New in Neural Networks
|
00:16:56 |
2017-03-06 04:27
|
|
|
Stein's Paradox
|
00:27:02 |
2017-02-27 03:51
|
|
|
Empirical Bayes
|
00:18:57 |
2017-02-20 04:30
|
|
|
Endogenous Variables and Measuring Protest Effectiveness
|
00:16:28 |
2017-02-13 04:31
|
|
|
Calibrated Models
|
00:14:32 |
2017-02-06 02:56
|
|
|
Rock the ROC Curve
|
00:15:52 |
2017-01-30 04:38
|
|
|
Ensemble Algorithms
|
00:13:08 |
2017-01-23 03:31
|
|
|
How to evaluate a translation: BLEU scores
|
00:17:06 |
2017-01-16 02:59
|
|
|
Zero Shot Translation
|
00:25:32 |
2017-01-09 04:20
|
|
|
Google Neural Machine Translation
|
00:18:12 |
2017-01-02 02:44
|
|
|
Data and the Future of Medicine : Interview with Precision Medicine Initiative researcher Matt Might
|
00:34:54 |
2016-12-26 02:19
|
|
|
Special Crossover Episode: Partially Derivative interview with White House Data Scientist DJ Patil
|
00:46:09 |
2016-12-18 18:53
|
|
|
How to Lose at Kaggle
|
00:17:16 |
2016-12-12 05:28
|
|
|
Attacking Discrimination in Machine Learning
|
00:23:20 |
2016-12-05 04:38
|
|
|
Recurrent Neural Nets
|
00:12:36 |
2016-11-28 03:47
|
|
|
Stealing a PIN with signal processing and machine learning
|
00:16:55 |
2016-11-21 03:32
|
|
|
Neural Net Cryptography
|
00:16:16 |
2016-11-14 05:06
|
|
|
Deep Blue
|
00:20:05 |
2016-11-07 05:20
|
|
|
Organizing Google's Datasets
|
00:15:00 |
2016-10-31 03:17
|
|
|
Fighting Cancer with Data Science: Followup
|
00:25:48 |
2016-10-24 03:58
|
|
|
The 19-year-old determining the US election
|
00:12:28 |
2016-10-17 03:01
|
|
|
How to Steal a Model
|
00:13:36 |
2016-10-10 00:57
|
|
|
Regularization
|
00:17:27 |
2016-10-03 04:13
|
|
|
The Cold Start Problem
|
00:15:37 |
2016-09-26 04:24
|
|
|
Open Source Software for Data Science
|
00:20:05 |
2016-09-19 06:27
|
|
|
Scikit + Optimization = Scikit-Optimize
|
00:15:41 |
2016-09-12 03:54
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Two Cultures: Machine Learning and Statistics
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00:17:29 |
2016-09-05 03:50
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Optimization Solutions
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00:20:07 |
2016-08-29 04:01
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Optimization Problems
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00:17:50 |
2016-08-22 02:25
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Multi-level modeling for understanding DEADLY RADIOACTIVE GAS
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00:23:34 |
2016-08-15 03:49
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How Polls Got Brexit "Wrong"
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00:15:14 |
2016-08-08 03:37
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Election Forecasting
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00:28:59 |
2016-08-01 04:40
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Machine Learning for Genomics
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00:20:22 |
2016-07-25 04:14
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Climate Modeling
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00:19:49 |
2016-07-18 04:26
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Reinforcement Learning Gone Wrong
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00:28:16 |
2016-07-11 04:42
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Reinforcement Learning for Artificial Intelligence
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00:18:30 |
2016-07-03 20:28
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Differential Privacy: how to study people without being weird and gross
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00:18:17 |
2016-06-27 03:53
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How the sausage gets made
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00:29:13 |
2016-06-20 04:25
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SMOTE: makin' yourself some fake minority data
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00:14:37 |
2016-06-13 05:06
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Conjoint Analysis: like AB testing, but on steroids
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00:18:27 |
2016-06-06 04:13
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Traffic Metering Algorithms
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00:17:30 |
2016-05-30 03:57
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Um Detector 2: The Dynamic Time Warp
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00:14:00 |
2016-05-23 04:05
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Inside a Data Analysis: Fraud Hunting at Enron
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00:30:28 |
2016-05-16 04:36
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What's the biggest #bigdata?
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00:25:31 |
2016-05-09 03:28
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Data Contamination
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00:20:58 |
2016-05-02 04:24
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Model Interpretation (and Trust Issues)
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00:16:57 |
2016-04-25 02:45
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Updates! Political Science Fraud and AlphaGo
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00:31:43 |
2016-04-18 04:48
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Ecological Inference and Simpson's Paradox
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00:18:32 |
2016-04-11 04:43
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Discriminatory Algorithms
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00:15:21 |
2016-04-04 04:30
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Recommendation Engines and Privacy
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00:31:33 |
2016-03-28 04:46
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Neural nets play cops and robbers (AKA generative adverserial networks)
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00:18:56 |
2016-03-21 03:58
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A Data Scientist's View of the Fight against Cancer
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00:19:08 |
2016-03-14 04:26
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Congress Bots and DeepDrumpf
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00:20:47 |
2016-03-11 05:17
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Multi - Armed Bandits
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00:11:29 |
2016-03-07 03:44
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Experiments and Messy, Tricky Causality
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00:16:59 |
2016-03-04 04:54
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Backpropagation
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00:12:21 |
2016-02-29 04:58
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Text Analysis on the State Of The Union
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00:22:22 |
2016-02-26 04:51
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Paradigms in Artificial Intelligence
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00:17:20 |
2016-02-22 05:32
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Survival Analysis
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00:15:21 |
2016-02-19 04:44
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Gravitational Waves
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00:20:26 |
2016-02-15 03:46
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The Turing Test
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00:15:15 |
2016-02-12 05:11
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Item Response Theory: how smart ARE you?
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00:11:46 |
2016-02-08 04:37
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Go!
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00:19:59 |
2016-02-05 05:52
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Great Social Networks in History
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00:12:42 |
2016-02-01 05:22
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How Much to Pay a Spy (and a lil' more auctions)
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00:16:59 |
2016-01-29 06:36
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Sold! Auctions (Part 2)
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00:17:27 |
2016-01-25 03:58
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Going Once, Going Twice: Auctions (Part 1)
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00:12:39 |
2016-01-22 04:40
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Chernoff Faces and Minard Maps
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00:15:11 |
2016-01-18 04:38
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t-SNE: Reduce Your Dimensions, Keep Your Clusters
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00:16:55 |
2016-01-15 05:05
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The [Expletive Deleted] Problem
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00:09:54 |
2016-01-11 05:23
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Unlabeled Supervised Learning--whaaa?
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00:12:35 |
2016-01-08 04:26
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Hacking Neural Nets
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00:15:28 |
2016-01-05 03:56
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Zipf's Law
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00:11:43 |
2015-12-31 19:08
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Indie Announcement
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00:01:19 |
2015-12-30 16:57
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Portrait Beauty
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00:11:44 |
2015-12-27 14:34
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The Cocktail Party Problem
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00:12:04 |
2015-12-18 01:17
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A Criminally Short Introduction to Semi Supervised Learning
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00:09:12 |
2015-12-04 04:13
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Thresholdout: Down with Overfitting
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00:15:52 |
2015-11-27 18:55
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The State of Data Science
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00:15:40 |
2015-11-10 05:36
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Data Science for Making the World a Better Place
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00:09:31 |
2015-11-06 04:43
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Kalman Runners
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00:14:42 |
2015-10-29 04:10
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Neural Net Inception
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00:15:19 |
2015-10-23 04:25
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Benford's Law
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00:17:42 |
2015-10-16 05:30
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Guinness
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00:14:43 |
2015-10-07 05:30
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PFun with P Values
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00:17:07 |
2015-09-02 05:24
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Watson
|
00:15:36 |
2015-08-25 04:26
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Bayesian Psychics
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00:11:44 |
2015-08-18 02:05
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Troll Detection
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00:12:57 |
2015-08-07 22:56
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Yiddish Translation
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00:12:15 |
2015-08-03 05:06
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Modeling Particles in Atomic Bombs
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00:15:38 |
2015-07-07 01:30
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Random Number Generation
|
00:10:26 |
2015-06-19 20:49
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Electoral Insights (Part 2)
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00:21:18 |
2015-06-09 04:46
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Electoral Insights (Part 1)
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00:09:17 |
2015-06-05 22:38
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Falsifying Data
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00:17:46 |
2015-06-01 23:04
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Reporter Bot
|
00:11:15 |
2015-05-21 01:16
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Careers in Data Science
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00:16:35 |
2015-05-16 07:43
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That's "Dr Katie" to You
|
00:03:01 |
2015-05-14 19:37
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Neural Nets (Part 2)
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00:10:55 |
2015-05-11 16:37
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Neural Nets (Part 1)
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00:09:00 |
2015-05-01 20:59
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Inferring Authorship (Part 2)
|
00:14:04 |
2015-04-28 18:56
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Inferring Authorship (Part 1)
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00:08:51 |
2015-04-16 19:25
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Statistical Mistakes and the Challenger Disaster
|
00:13:09 |
2015-04-06 21:36
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Genetics and Um Detection (HMM Part 2)
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00:14:49 |
2015-03-25 18:29
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Introducing Hidden Markov Models (HMM Part 1)
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00:14:54 |
2015-03-24 16:57
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Monte Carlo For Physicists
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00:08:13 |
2015-03-13 00:18
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Random Kanye
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00:08:44 |
2015-03-05 00:04
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Lie Detectors
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00:09:17 |
2015-02-25 19:20
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The Enron Dataset
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00:12:27 |
2015-02-09 01:00
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Labels and Where To Find Them
|
00:13:15 |
2015-02-04 03:30
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Um Detector 1
|
00:13:19 |
2015-01-23 21:16
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Better Facial Recognition with Fisherfaces
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00:11:56 |
2015-01-07 02:33
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Facial Recognition with Eigenfaces
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00:10:01 |
2015-01-07 02:30
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Stats of World Series Streaks
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00:12:34 |
2014-12-17 01:41
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Computers Try to Tell Jokes
|
00:09:08 |
2014-11-26 19:59
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How Outliers Helped Defeat Cholera
|
00:10:54 |
2014-11-22 01:00
|
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Hunting for the Higgs
|
00:10:16 |
2014-11-16 01:00
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