Andriy Burkov
1 books with highlights
Books
The Hundred-Page Machine Learning Book
20 highlights
Featured Highlights
Overfitting occurs when a model learns the training data too well, including its noise.
Machine learning is a field of study that gives computers the ability to learn without being explicitly programmed.
Deep learning models have gained popularity due to their ability to learn complex patterns in large datasets.
Regularization techniques help prevent overfitting.
The bias-variance tradeoff is a central concept in machine learning.
A good model is one that generalizes well to unseen data.
Regularization is a technique used to prevent overfitting by adding a penalty on the size of coefficients.
Overfitting occurs when a model learns the noise in the training data.
The most important part of building a machine learning model is to understand the problem you are trying to solve.
Hyperparameter tuning can significantly affect the performance of your model.