paper-summary machine-learning-engineering technical-debt
Paper Summary: Hidden Technical Debt in Machine Learning Systems
23 Mar 2020 Summary of the 2015 article "Hidden Technical Debt in Machine Learning Systems" by Sculley et al.
Scikit-learn Pipelines: Custom Transformers and Pandas integration
08 Mar 2020 Examples and reference on how to write customer transformers and how to create a single sklearn pipeline including both preprocessing steps and classifiers at the end, in a way that enables you to use pandas dataframes directly in a call to fit.
Numpy Sampling: Reference and Examples
07 Mar 2020 Sample from probability distributions and from lists, with and without weights. Examples using Python, Numpy and Scipy.
Read More ›Spark dataframe Examples: Reading and Writing Dataframes
23 Feb 2020 Some examples on how to read and write spark dataframes from sources such as S3 and databricks file systems.
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Paper Summary: Software Engineering for Machine Learning: A Case Study
25 Jan 2020 Summary of the 2019 article "Software Engineering for Machine Learning: A Case Study" by Amershi et al.
Git branching: Reference and Examples
23 Jan 2020 Common use cases and examples for using branches on git, locally and on remotes.
Read More ›paper-summary attention sequence-learning machine-translation
Paper Summary: Neural Machine Translation by Jointly Learning to Align and Translate
11 Jan 2020 Summary of the 2014 article "Neural Machine Translation by Jointly Learning to Align and Translate" by Bahdanau et al.
paper-summary machine-learning-engineering
Paper Summary: Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift
23 Dec 2019 Summary of the 2019 article "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift" by Rabanser et al.
Python Unittest Examples: Mocking and Patching
09 Dec 2019 Simple examples to help you understand when/where to use mocking and patching, so you don't need to skip testing any part of your code.
Read More ›Pandas Dataframe Examples: Duplicated Data
17 Nov 2019 Deal with duplicated data in pandas: drop, count, show and mark duplicates in pandas dataframes.