Quick Overview: Residual Networks, DenseNet, Recurrent Neural Networks. Slides and materials on the course website: ... Logistic Regression, linear SVMs, the kernel trick One-vs-Rest and One-vs-One multi-class strategies. Class website with slides ... A quick recap and Q & A on some of the main points of the second half of the course.
Applied Machine Learning 2019 Lecture - Detailed Overview & Context
Residual Networks, DenseNet, Recurrent Neural Networks. Slides and materials on the course website: ... Logistic Regression, linear SVMs, the kernel trick One-vs-Rest and One-vs-One multi-class strategies. Class website with slides ... A quick recap and Q & A on some of the main points of the second half of the course. Latent Semantic Analysis, Non-negative Matrix Factorization for Topic models, Latent Dirichlet Allocation Markov Chain Monte ... Text data, bag of words, n-grams, tfidf, stop words, text classification. More information on the class website: ... About this Course this course will introduce the learner to
Time series formats and tasks Stationarity Seasonal Models Autoregressive models More materials and slides on the course ... CBOW, skip-grams, Word2Vec, paragraph vectors Gradient descent and stochastic gradient descent Class website with slides ... Basics of git and github, introduction to unit testing and continuous integration Materials on the course website: ...
