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Career Coaching for Data Professionals
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Bartosz Mikulski
Building trustworthy data pipelines because AI cannot learn from dirty data
All Stories
How to increase accuracy of a deep learning model
Debugging a machine learning model
Smoothing time series in Pandas
How to use the exponentially weighted window functions in Pandas
Which hyperparameters of deep learning model are important and how to find them
How to speed up finding the right hyperparameters of a machine learning model
How to choose the right mini-batch size in deep learning
How to deal with underfitting and overfitting in deep learning
The lessons learned from Andrew Ng’s online course
How to reduce memory usage in Pandas
Fit more data in the same amount of memory
How Airflow scheduler works
Explanation of the Airflow interval and start_date parameters
Guidelines for data science teams — a summary of Daniel Molnar’s talks
Avoiding over-engineering in machine learning
Ludwig machine learing model in Kaggle
My first attempt to use Ludwig
The problem of large categorical variables in machine learning
How to use FeatureHasher in Scikit-learn
Encoding categorical variables in machine learning
One-hot encoding, dummy coding, and effect coding in Scikit learn and Pandas
How To Avoid Data Leakage While Building A Machine Learning Model
What to do when your model works perfectly during testing but fails in production
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