AWS
bash
Caffe
cloud
- Try Caffe pre-installed on a VirtualBox image
- Start deep learning with Jupyter notebooks in the cloud
- A review of the online course “Introduction to Big Data with Apache Spark”
conda
database
deep learning
- Introduction to OpenAI Scholars 2020
- Try Caffe pre-installed on a VirtualBox image
- Start deep learning with Jupyter notebooks in the cloud
Jupyter
- Try Caffe pre-installed on a VirtualBox image
- Start deep learning with Jupyter notebooks in the cloud
kernel methods
linselect
- Linear compression in python: PCA vs unsupervised feature selection
- linselect demo: a tech sector stock analysis
machine learning
- Long term credit assignment with temporal reward transport
- Q-learning and DQN
- Dynamic programming in reinforcement learning
- Introduction to reinforcement learning by example
- Multiarmed bandits in the context of reinforcement learning
- Introduction to OpenAI Scholars 2020
- Support Vector Machines for classification
- Machine learning for facial recognition
- Machine learning with wearable sensors
- Traffic patterns of the year: 2014 edition
methods
- Linear compression in python: PCA vs unsupervised feature selection
- Gaussian Processes
- Getting started with Pandas
- Build a web scraper for a literature search - from soup to nuts
- Quantifying the NBA Christmas week flop: one in ten thousand?
- Machine Learning Methods: Classification without negative examples
- NBA learner: 2013-14 warmup
- Data reduction by PCA
mooc
NBA
- NBA week 9 summary, week 10 predictions
- NBA week 8 results, week 9 predictions
- Quantifying the NBA Christmas week flop: one in ten thousand?
- NBA week 7 results, week 8 predictions
- NBA week 6 results, week 7 predictions, intro to dash
- NBA week 5 summary, week 6 predictions
- NBA week 4 summary, week 5 predictions
- NBA week 3 summary, week 4 predictions
- NBA week 2 summary, week 3 predictions
- NBA week 1 summary, week 2 predictions
- NBA weekly predictions: up
- NBA learner: 2013-14 warmup
- Announcing: NBA learner v0.1
OpenAI
- Long term credit assignment with temporal reward transport
- Q-learning and DQN
- Introduction to reinforcement learning by example
- Introduction to OpenAI Scholars 2020
optimization
programming
- Visualizing an actor critic algorithm in real time
- TimeMarker class for python
- Gaussian Processes
- Dotfiles for peace of mind
- Getting started with Pandas
- Reshaping Data in R
- Processing and processing.js tips and tricks in WordPress
- NBA week 6 results, week 7 predictions, intro to dash
- Obtaining and visualizing traffic data
python
- To Flourish or to Perish
- Visualizing an actor critic algorithm in real time
- 2-D random walks are special
- A Framework for Studying Population Dynamics
- TimeMarker class for python
- Linear compression in python: PCA vs unsupervised feature selection
- Support Vector Machines for classification
quadratic programming
R
reinforcement learning
- Long term credit assignment with temporal reward transport
- Visualizing an actor critic algorithm in real time
- Q-learning and DQN
- Dynamic programming in reinforcement learning
- Introduction to reinforcement learning by example
- Multiarmed bandits in the context of reinforcement learning
- Introduction to OpenAI Scholars 2020
review
spark
SQL
statistics
- Generalized Dollar Cost Averaging
- To Flourish or to Perish
- 2-D random walks are special
- A Framework for Studying Population Dynamics
- Gaussian Processes
- Normal Distributions
- Interpreting the results of linear regression
- Stochastic geometric series
- Quantifying the NBA Christmas week flop: one in ten thousand?
SVM
theory
- Generalized Dollar Cost Averaging
- The speed of traffic
- Gaussian Processes
- Martingales
- Normal Distributions
tools
- Visualizing an actor critic algorithm in real time
- TimeMarker class for python
- Dotfiles for peace of mind
- Getting started with Pandas
- Build a web scraper for a literature search - from soup to nuts
traffic
- The speed of traffic
- Historic daily traffic patterns and the time scale of deviations
- Daily traffic evolution and the Super Bowl
- Data reduction by PCA
- Traffic patterns of the year: 2014 edition
- Obtaining and visualizing traffic data