Applied Machine Learning
This channel contains videos on Applied Machine Learning from the courses taught at the University of British Columbia by Varada Kolhatkar. Happy learning!
Introduction to Self-Attention [Applied Machine Learning || Varada Kolhatkar || UBC]
18.3 Word2vec [Applied Machine Learning || Varada Kolhatkar || UBC]
18.2 Term-term Cooccurrence Matrix [Applied Machine Learning || Varada Kolhatkar || UBC]
18.1 Word Embeddings Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
17.3 PCA Loss [Applied Machine Learning || Varada Kolhatkar || UBC]
17.2 PCA Intuition and Terminology [Applied Machine Learning || Varada Kolhatkar || UBC]
17.1 Dimensionality Reduction Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
15.3 Hierarchical Clustering [Applied Machine Learning || Varada Kolhatkar || UBC]
15.2 DBSCAN [Applied Machine Learning || Varada Kolhatkar || UBC]
15.1 DBSCAN Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
9.1 Classification Metrics Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
16.2 Text Preprocessing [Applied Machine Learning || Varada Kolhatkar || UBC]
16.1 What is NLP? [Applied Machine Learning || Varada Kolhatkar || UBC]
14.3 K-Means: Choosing K [Applied Machine Learning || Varada Kolhatkar || UBC]
14.2 K-Means Algorithm [Applied Machine Learning || Varada Kolhatkar || UBC]
14.1 Clustering Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
12.2 Feature Importances Non-Linear Models [Applied Machine Learning || Varada Kolhatkar || UBC]
12.1 Model Interpretation Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
11.2 Intro to Gradient Boosted Tree Models [Applied Machine Learning || Varada Kolhatkar || UBC]
11.1 Ensembles: Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
10.1 Preprocessing Housing Price Dataset [Applied Machine Learning || Varada Kolhatkar || UBC]
9.4 Addressing Class Imbalance [Applied Machine Learning || Varada Kolhatkar || UBC]
9.3 Precision, Recall, F1 score [Applied Machine Learning || Varada Kolhatkar || UBC]
9.2 Confusion Matrix [Applied Machine Learning || Varada Kolhatkar || UBC]
8.2 Overfitting of the validation error [Applied Machine Learning || Varada Kolhatkar || UBC]
8.1 Hyperparameter Optimization Motivation [Applied Machine Learning || Varada Kolhatkar || UBC]
7.3 Predicting Probability Scores [Applied Machine Learning || Varada Kolhatkar || UBC]
7.2 Logistic Regression [Applied Machine Learning || Varada Kolhatkar || UBC]
7.1 Linear Regression [Applied Machine Learning || Varada Kolhatkar || UBC]
6.2 Encoding Text Features [Applied Machine Learning || Varada Kolhatkar || UBC]