AI
- Active learning and deep probabilistic ensembles
- Image Search Take 2 - Convolutional Autoencoders
- An Overview of Attention Is All You Need
- Image search with autoencoders
Active Learning
Attention
- Deep learning for tabular data 2 - Debunking the myth of the black box
- An Overview of Attention Is All You Need
Auto Encoders
Bayesian Inference
- What is the posterior and why does it matter?
- Forecasting the final 100 or so games for all 30 MLB teams
- PyMCon Afterword
- PyMCon Foreward
- MLB 2020 Postseason Projections
- My Quarantine Playlist
- Predicting Pete Alonso's 2020 Performance
- 2019 World Series Pitcher Matchups
- Active learning and deep probabilistic ensembles
- World Series Projections
- Hierarchical Bayesian Ranking
- Hypothesis Testing For Humans - Do The Umps Really Want to Go Home
- Bayesian Online Learning
- A brief primer on conjugate priors
Beginner
Deep Learning
- Deep Learning for Time Series
- Neural Networks Explained
- Deep learning for tabular data 2 - Debunking the myth of the black box
- Deep learning for tabular data
- Active learning and deep probabilistic ensembles
- Image Search Take 2 - Convolutional Autoencoders
- An Overview of Attention Is All You Need
- Image search with autoencoders
Images
- Clustering and Image Segmentation
- Image Search Take 2 - Convolutional Autoencoders
- Image search with autoencoders
Industry
- Model Evaluation For Humans
- Monitoring Machine Learning Models in Production
- From Docker to Kubernetes
Learning to Rank
MLB
- Forecasting the final 100 or so games for all 30 MLB teams
- Evaluating my 2020 MLB Predictions - Part 2, The Postseason
- Evaluating my 2020 MLB Predictions - Part 1, Pete Alonso
- MLB 2020 Postseason Projections
- Predicting Pete Alonso's 2020 Performance
- 2019 World Series Pitcher Matchups
- Deep learning for tabular data 2 - Debunking the myth of the black box
- World Series Projections
- Hierarchical Bayesian Ranking
- Hypothesis Testing For Humans - Do The Umps Really Want to Go Home
Machine Learning
- Scaling Predictions
- Clustering and Image Segmentation
- Know Your Trees
- Monitoring Machine Learning Models in Production
Model Evaluation
Model Evaluations
- Evaluating my 2020 MLB Predictions - Part 2, The Postseason
- Evaluating my 2020 MLB Predictions - Part 1, Pete Alonso
Monte Carlo
Online Learning
Opinion
- A Beginner's Guide to Why You Should or Shouldn't Be Using Kubernetes for Machine Learning (With Illustrations)
- Neural Networks Explained
- Keras Feature Columns
Projections
Recommendation Systems
- A Tutorial on Collaborative Filtering in sklearn
- Image Search Take 2 - Convolutional Autoencoders
- Image search with autoencoders
Software
Time Series
Variational Inference
World Series
docker
helm
keras
- Tensorflow 2 Feature Columns and Keras
- Image Search Take 2 - Convolutional Autoencoders
- Keras Feature Columns
- An Overview of Attention Is All You Need
- Image search with autoencoders
kubernetes
- A Beginner's Guide to Why You Should or Shouldn't Be Using Kubernetes for Machine Learning (With Illustrations)
- From Docker to Kubernetes
pandas
pymc
- What is the posterior and why does it matter?
- Forecasting the final 100 or so games for all 30 MLB teams
- PyMCon Afterword
- PyMCon Foreward
pymc3
- 2019 World Series Pitcher Matchups
- World Series Projections
- Hierarchical Bayesian Ranking
- Hypothesis Testing For Humans - Do The Umps Really Want to Go Home
sklearn
- A Tutorial on Collaborative Filtering in sklearn
- Clustering and Image Segmentation
- A fast one hot encoder with sklearn and pandas