Evaluating impact of interventions
Protect yourself from costly bandits
Protect yourself from costly bandits
Keras, the LEGO of deep learning
Helping a machine to make sense of tabular data
Visualising high-dimensional datasets
Summarising data using fewer features
Are you Frequently A / B testing?
The game of life
How to show off your random forest
The dangers of cherry picking evidence
How to tidy up multiple if and else if statements
Easy date aggregations
The prize winning, scalable, portable and distributed Gradient Boosting algorithm
Back to basics with Artificial Neural Networks
A supervised learning method motivated by an analogy to biological evolution
Letting testthat do the heavy lifting
Advanced Regression techniques for predicting house prices
Using Spark and R for regression of concrete strength
Quick and easy classification
Forecasting regime changes in market turbulence
Complex decisions made simple
Mapping obesity in the UK
My data science journey is a Markov Chain
Combining objects as data_frames in purrr
A simple non-linear classifier using nearest-neighbour averaging
Predicting survival of passengers on the Titanic
Linear models and least squares
Working with time series data and basic forecasting
Student attainment prediction with neural networks
What happens when Hadley reads your blog
Using dplyr, broom, and purrr to make life easy
Evaluating performance of supervised learning tools
Predicting forest fire scale using support vector machines
Predicting student end of year performance using logistic regression
Using character matching for quick lookups
Predicting student performance using CART
A year's data collected with a simple LDR based light sensor
Setting up minibian
A low cost Wi-Fi serial module
A year of measurements
Home monitoring with Raspberry Pis
A simple implementation
Writing papers for peer review with knitr
Making bubble maps in R
Using classes in R
Using R package glmnet for regularisation
Adding temperature monitoring to the equation
Using an arduino for environmental sensing
Adding regularisation to vectorised linear regression
Do Londoners and New Yorkers disagree?
Some lessons learned the hard way
Simple multiclass classification
Implementing regularisation and feature mapping
Comparing vectorised methods with general linear models
Feature scaling and gradient descent
Linear regression the machine learning way
Implementing gradient decsent in R
Blogger, WordPress, Jekyll?
ggvis workshop at LondonR by Aimee Gott
Using the Google routing API via ggmap
Gender differences in the New York cycle hire data