Tags

• #time-series

  • ARIMA, ARMA, what's the difference?
  • Solving Partial Autocorrelation Functions

• #statistics

  • Random Search for Hyper-Parameter Optimization
  • A Deep Hierarchical Approach to Lifelong Learning in Minecraft
  • Solving Partial Autocorrelation Functions

• #ARMA

  • ARIMA, ARMA, what's the difference?
  • Solving Partial Autocorrelation Functions

• #c++

  • Full example for using JSONcpp on Unix

• #json

  • Full example for using JSONcpp on Unix

• #example

  • Full example for using JSONcpp on Unix

• #algorithms

  • Do deep networks generalise or just memorise?
  • Excellent description of how hashtables work

• #papers

  • Pointer Networks
  • Outrageously Large Neural Networks: The sparsely-gated Mixture-of-Experts layer
  • Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
  • Random Search for Hyper-Parameter Optimization
  • A Deep Hierarchical Approach to Lifelong Learning in Minecraft
  • SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5mb model size
  • Conditional image synthesis with auxiliary classifier GANs
  • Generative Adversarial Imitation Learning
  • Representation Learning: A Review and New Perspectives
  • Full Resolution Image Compression with Recurrent Neural Networks
  • Generative Adversarial Networks and Actor-Critic methods
  • Using simulated data to train robots
  • Safe and Efficient Off-Policy Reinforcement Learning
  • XGBoost: A scalable tree boosting system

• #machine-learning

  • Pointer Networks
  • Outrageously Large Neural Networks: The sparsely-gated Mixture-of-Experts layer
  • Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour
  • SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5mb model size
  • Conditional image synthesis with auxiliary classifier GANs
  • Generative Adversarial Imitation Learning
  • Representation Learning: A Review and New Perspectives
  • Full Resolution Image Compression with Recurrent Neural Networks
  • Generative Adversarial Networks and Actor-Critic methods
  • Using simulated data to train robots
  • Safe and Efficient Off-Policy Reinforcement Learning
  • XGBoost: A scalable tree boosting system

• #python

  • Minimal example of how to do model selection in Python

• #machine

  • Random Search for Hyper-Parameter Optimization
  • How I designed my machine learning app
  • A Deep Hierarchical Approach to Lifelong Learning in Minecraft
  • Minimal example of how to do model selection in Python

• #learning

  • Random Search for Hyper-Parameter Optimization
  • How I designed my machine learning app
  • A Deep Hierarchical Approach to Lifelong Learning in Minecraft
  • Minimal example of how to do model selection in Python

• #consulting

  • Larry Ellison on consulting costs

• #oracle

  • Larry Ellison on consulting costs

• #softwar

  • Larry Ellison on consulting costs

• #web

  • Including web fonts in RMarkdown

• #html

  • Including web fonts in RMarkdown
  • Including web fonts in RMarkdown

• #rmd

  • Including web fonts in RMarkdown

• #rmarkdown

  • Including web fonts in RMarkdown

• #R

  • Including web fonts in RMarkdown

• #markdown

  • Including web fonts in RMarkdown

• #bash

  • Useful Bash One-liners

• #security

  • Securing yourself against online tracking

• #tech

  • The junior tech landscape

• #jobs

  • The junior tech landscape