Machine Learning: Dimensionality Reduction via Linear Discriminant Analysis
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. A machine learning algorithm (such as classification, clustering or regression) uses a training dataset to determine weight factors that can be applied to unseen data for predictive purposes. Before implementing a machine …
Where the randomness comes
Author(s): Jun Wang Originally published on Towards AI. Word Embedding and Language Modeling U+007C Towards AI How to Get Deterministic word2vec/doc2vec/paragraph Vectors OK, welcome to our Word Embedding Series. This post is the first story of the series. You may find this …
Machine Learning: Dimensionality Reduction via Principal Component Analysis
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. How does PCA work? In machine learning, a dataset containing features (predictors) and discrete class labels (for a classification problem such as logistic regression); or features and continuous outcomes (for a linear …
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