Single frame summaries of must-know DS/ML concepts and techniques.
Understanding scaling and standardization from the perspective of skewness.
Decision trees always overfit. Prevent it this way.
An untaught advantage of L2 regularization that most data scientists don't know.
From "ML model developer" to "ML engineer."
Transcript, sentiment analysis, speaker labels, topics, Q&A, all in one place.
A single frame summary.
What happens when you instantiate a new object?
A simple technique, and some key considerations.
75 key terms all data scientists should know.
The surprising phenomena that arise when dealing with data in high dimensions.
