Episodes
The intuition behind loss function
Published 12/13/21
Published 12/13/21
A quick introduction to central limit theorem and why it helps data analysis
Published 12/04/21
Thoughts on causality and the need for a control sample
Published 12/03/21
Can we think of neural networks as layers of decisions with regression and classification at each layer?
Published 12/01/21
What are the different types of data attributes?
Published 11/29/21
Independence of the dependent variable
Published 11/23/21
Generalizing the estimations of population parameters
Published 11/23/21
Guessing the recipe of data!
Published 11/19/21
How are decision trees trained and what is entropy?
Published 11/19/21
What is the intuition behind cross-validation for estimating population parameters?
Published 11/17/21
What is a population and what is a sample? What exactly do we want to do with them?
Published 11/16/21
What is Machine Learning? What are supervised and unsupervised machine learning methods?
Published 11/16/21
What is cosine similarity in multidimensional data?
Published 11/12/21
What is PCA and what does it do?
Published 11/11/21
Intuition behind latent features in singular value decomposition
Published 11/09/21
Building recommendation systems using content - features of users and items
Published 11/08/21
Building recommendation systems using observed interaction data
Published 11/04/21
Why are recommendation systems important and how they are built?
Published 11/04/21