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