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A Pivotal Moment in NLP Research Which Made Static Embeddings (Almost) Obsolete

A Pivotal Moment in NLP Research Which Made Static Embeddings (Almost) Obsolete

Looking back to the pre-Transformer times.

Don't Make This Blunder When Using Multiple Embedding Models in Your ML Pipeline

Don't Make This Blunder When Using Multiple Embedding Models in Your ML Pipeline

Here's a mistake that often goes unnoticed.

8 Automated EDA Tools That Reduce Plenty of Manual EDA Hard Work

8 Automated EDA Tools That Reduce Plenty of Manual EDA Hard Work

8 automated EDA tools in a single frame.

An Overlooked Source of (Massive) Run-time Optimization in KMeans

An Overlooked Source of (Massive) Run-time Optimization in KMeans

Another issue with KMeans and here's how to address it.

How Does a Mini-Batch Implementation of KMeans Clustering Work?

How Does a Mini-Batch Implementation of KMeans Clustering Work?

A step-by-step visual guide to mini-batch KMeans.

The Most Common Way a Continuous Probability Distribution is Misinterpreted

The Most Common Way a Continuous Probability Distribution is Misinterpreted

The difference between probability density function and probability.

5 Must-know Cross Validation Techniques Explained Visually

5 Must-know Cross Validation Techniques Explained Visually

A 2-min visual guide to popular cross validation techniques.

You Can Build Any Linear Model If You Learn Just One Thing About Them

You Can Build Any Linear Model If You Learn Just One Thing About Them

The most underappreciated skill in building linear models.

The Modeling Limitations of Linear Regression Which Poisson Regression Addresses

The Modeling Limitations of Linear Regression Which Poisson Regression Addresses

Linear regression is not the only linear model.

GROUPING SETS — A HIGHLY Underrated Technique to Run Multiple Aggregations While Scanning the Table Only Once

GROUPING SETS — A HIGHLY Underrated Technique to Run Multiple Aggregations While Scanning the Table Only Once

A lesser-known and much efficient way to run multiple aggregations.

Why is OLS Called an Unbiased Estimator?

Why is OLS Called an Unbiased Estimator?

Along with a common misconception about unbiasedness.

Why Sklearn's Linear Regression Implementation Has No Hyperparameters?

Why Sklearn's Linear Regression Implementation Has No Hyperparameters?

What are we missing here?

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