The Productive Machine Learning Engineer
  • All Posts
  • Common Pitfalls
  • Model Compression
  • Feature Selection
  • Data Valuation
  • Documentation
  • GitHub
Get Your API Key
Subscribe Get Your API Key
  • All Posts
  • Common Pitfalls
  • Model Compression
  • Feature Selection
  • Data Valuation
  • Documentation
  • GitHub

featured story

How I Got In The Top 1% of A Kaggle Competition With kxy And No Hyper-Parameter Tuning

The solution that ranked 26th/1946 in the G-Research Crypto Forecasting Kaggle competition.

9 May 2022 · 6 min read
Read post
How I Got In The Top 1% of A Kaggle Competition With kxy And No Hyper-Parameter Tuning

featured story

Boruta(SHAP) Does Not Work For The Reason You Think It Does!

Everything you wish you knew about Boruta, and more.

3 May 2022 · 8 min read
Read post
Boruta(SHAP) Does Not Work For The Reason You Think It Does!

featured story

Autoencoders: What Are They, and Why You Should Never Use Them For Pre-Processing

Fundamental limitations you need to be aware of before using autoencoders as pre-processing step in predictive modeling problems on tabular data.

19 Apr 2022 · 14 min read
Read post
Autoencoders: What Are They, and Why You Should Never Use Them For Pre-Processing
How I Got In The Top 1% of A Kaggle Competition With kxy And No Hyper-Parameter Tuning
LeanML Feature Selection

How I Got In The Top 1% of A Kaggle Competition With kxy And No Hyper-Parameter Tuning

The solution that ranked 26th/1946 in the G-Research Crypto Forecasting Kaggle competition.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
9 May 2022 · 6 min read
Boruta(SHAP) Does Not Work For The Reason You Think It Does!
Boruta

Boruta(SHAP) Does Not Work For The Reason You Think It Does!

Everything you wish you knew about Boruta, and more.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
3 May 2022 · 8 min read
Autoencoders: What Are They, and Why You Should Never Use Them For Pre-Processing
Common Pitfalls

Autoencoders: What Are They, and Why You Should Never Use Them For Pre-Processing

Fundamental limitations you need to be aware of before using autoencoders as pre-processing step in predictive modeling problems on tabular data.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
19 Apr 2022 · 14 min read
How To Fix PCA To Make It Work For Feature Selection
Principal Feature Selection

How To Fix PCA To Make It Work For Feature Selection

Introducing Principal Feature Selection (With Code)

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
8 Apr 2022 · 9 min read
5 Reasons You Should Never Use PCA For Feature Selection
Common Pitfalls

5 Reasons You Should Never Use PCA For Feature Selection

Fundamental limitations you need to be aware of before using Principal Components Analysis for feature selection.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
31 Mar 2022 · 7 min read
Feature Engineering With Game Theory: Beyond SHAP values
Feature Selection

Feature Engineering With Game Theory: Beyond SHAP values

Understanding the difference between feature importance, feature usefulness, and feature potential using Shapley values.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
23 Mar 2022 · 7 min read
5 Reasons Why You Should Never Use Recursive Feature Elimination
Common Pitfalls

5 Reasons Why You Should Never Use Recursive Feature Elimination

Fundamental limitations you need to be aware of before using Recursive Feature Elimination (RFE) or any other feature selection algorithm based on feature importance.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
15 Mar 2022 · 4 min read
AutoML: How To Reduce Your Model Size by 95% While Improving Model Performance
Model Compression

AutoML: How To Reduce Your Model Size by 95% While Improving Model Performance

We show you how to reduce the number of features used by AWS' AutoGluon tabular models in Python by 95% while improving model performance.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
8 Mar 2022 · 10 min read
Random Forest: How To Reduce Your Production Model Size by 95%
Model Compression

Random Forest: How To Reduce Your Production Model Size by 95%

We show you how to reduce the number of features used by your Random Forest model in Python by 95%, at no performance cost.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
8 Mar 2022 · 7 min read
XGBoost: How To Reduce Your Production Model Size by 95%
Model Compression

XGBoost: How To Reduce Your Production Model Size by 95%

We show you how to reduce the number of features used by your XGBoost model in Python by 95%, at no performance cost.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
7 Mar 2022 · 7 min read
LightGBM: How To Reduce Your Production Model Size by 95%
Model Compression

LightGBM: How To Reduce Your Production Model Size by 95%

We show you how to reduce the number of features used by your LightGBM model in Python by 95%, at no performance cost.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
6 Mar 2022 · 7 min read
How To Seamlessly Compress Any Tabular Model in Python
Model Compression

How To Seamlessly Compress Any Tabular Model in Python

Train your favorite predictive models in Python (e.g. LightGBM, XGBoost, Scikit-Learn, Tensorflow, and PyTorch models) using at least 80% fewer features, at no performance cost.

  • Go to the profile of  Yves-Laurent Kom Samo, PhD
Yves-Laurent Kom Samo, PhD
4 Feb 2022 · 18 min read
© 2023 The Productive Machine Learning Engineer. All rights reserved.
  • All Posts
  • Common Pitfalls
  • Model Compression
  • Feature Selection
  • Data Valuation
  • Documentation
  • GitHub
  • Get Your API Key

About Us

Tutorials, Thoughts & Ideas on How To Speed-Up Your Machine Learning Projects

Tags

Feature Selection
Automating Feature Engineering
LeanML Feature Selection
Model Compression
Getting Started

Subscribe

Get the latest tutorials on achieving better machine learning results, faster and cheaper.

Great! Check your inbox and click the link to confirm your subscription
Please enter a valid email address!
© 2023 The Productive Machine Learning Engineer. All rights reserved.
  • All Posts
  • Common Pitfalls
  • Model Compression
  • Feature Selection
  • Data Valuation
  • Documentation
  • GitHub
  • Get Your API Key
No results found
↑ ↓ Navigate up/down
Enter Go to article
Esc Close search