Course Details

Course details of EE5705
Course NoEE5705
Course TitleData Analytics Lab
Course ContentIntroduction to various Python toolkits: Numpy for handling arrays and matrices; SciPy for scientific computing; Matplotlib for data visualization; Pandas for data manipulation; SciKit Learn library for machine learning. Linear models for regression: Ordinary least squares; Ridge regression (l2 regularization); Lasso (l1 regularization); Elastic Net (l2-l1 regularization). Linear classification: Naive Bayes, Linear Discriminant Analysis (LDA); Logistics regression; Linear Support Vector Machine (SVM); l2 and l1 regularized versions of these algorithms. Non-linear algorithms: Kernel SVM, Random forest. Gradient Boosting, Neural network. Unsupervised learning: Dimensionality reduction techniques such as Principal Component Analysis (PCA), Clustering techniques such as k-Means clustering and Agglomerative clustering.
Course Offered this semesterNo
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