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Explorez tous les épisodes du podcast intuitions behind Data Science

Plongez dans la liste complète des épisodes de intuitions behind Data Science. Chaque épisode est catalogué accompagné de descriptions détaillées, ce qui facilite la recherche et l'exploration de sujets spécifiques. Suivez tous les épisodes de votre podcast préféré et ne manquez aucun contenu pertinent.

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1–18 of 18

TitreDateDurée
Loss Function13 Dec 202100:06:13
The intuition behind loss function
Central Limit Theorem04 Dec 202100:05:21
A quick introduction to central limit theorem and why it helps data analysis
Ground Truths in Data Science16 Nov 202100:08:19
What is a population and what is a sample? What exactly do we want to do with them?
Thoughts on Machine Learning16 Nov 202100:06:23
What is Machine Learning? What are supervised and unsupervised machine learning methods?
Cosine Similarity12 Nov 202100:08:46
What is cosine similarity in multidimensional data?
Principal Component Analysis11 Nov 202100:10:46
What is PCA and what does it do?
Latent Features09 Nov 202100:10:29
Intuition behind latent features in singular value decomposition
Recommendation Systems Using Content08 Nov 202100:08:15
Building recommendation systems using content - features of users and items
Recommendation Systems Using Observed Data04 Nov 202100:09:49
Building recommendation systems using observed interaction data
Recommendation Systems04 Nov 202100:06:53
Why are recommendation systems important and how they are built?
Causality and Control03 Dec 202100:07:02
Thoughts on causality and the need for a control sample
Neural Networks01 Dec 202100:08:34
Can we think of neural networks as layers of decisions with regression and classification at each layer?
Types of Data Attributes29 Nov 202100:13:00
What are the different types of data attributes?
Intercept23 Nov 202100:07:29
Independence of the dependent variable
Bias and Variance23 Nov 202100:06:20
Generalizing the estimations of population parameters
Linear Regression19 Nov 202100:07:02
Guessing the recipe of data!
Decision Trees and Entropy19 Nov 202100:06:29
How are decision trees trained and what is entropy?
Validation17 Nov 202100:09:04
What is the intuition behind cross-validation for estimating population parameters?
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