Tag: Sklearn

Learn about 19 Sklearn features you have never seen that are direct and elegant replacements to common operations you do manually.   Image by me with Midjourney Introduction After three years of use and by looking at the API reference of Sklearn, I have realized that the m...

Being a data scientist demands expertise in plenty of areas. You need to be good at using appropriate tools, like Pandas, NumPy, Sklearn, etc. These are indispensable to the development life cycle of many data-driven projects, making them essential skills to begin/maintain a career in data scienc...

Today, this is what I am selling: awesome_pipeline.fit(X, y) awesome_pipeline may look just like another variable, but here is what it does to poor X and y under the hood: Automatically isolates numerical and categorical features of X. Imputes missing va...

Basically, cross-validation is a statistical method for evaluating learning algorithms. A fixed number of folds (groups of data) is set to run the analysis. These folds group the data into 2 sets: training and testing (validation) sets, that are cross-over in rounds, allowing each data point to be v...

Learn to avoid the six most serious mistakes related to machine learning theory that beginners often make through Sklearn. Image by me with Leonardo AI Often, Sklearn throws big red error messages and warnings when you make a mistake. These messages suggest something is seriously wrong wit...

Learn to avoid the six most serious mistakes related to machine learning theory that beginners often make through Sklearn. Image by me with Leonardo AI Often, Sklearn throws big red error messages and warnings when you make a mistake. These messages suggest something is seriously wrong wit...

Being a data scientist demands expertise in plenty of areas. You need to be good at using appropriate tools, like Pandas, NumPy, Sklearn, etc. These are indispensable to the development life cycle of many data-driven projects, making them essential skills to begin/maintain a career in data scienc...