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Learn Machine | Best Tutorials and Courses
Taught By: Andrew Ng
Description: You will learn about Machine Learning basics, Linear Regression with One Variable, Basics of Linear Algebra, Linear Regression with Multiple Variables, Logistic Regression, Regularization, Neural Networks, Support Vector Machines, Unsupervised Learning, Dimensionality Reduction, Anomaly Detection, Recommender Systems, Photo OCR, etc.
Prerequisite: Basic knowledge in Machine Learning would be helpful, but not required.
Taught By: Kirill Eremenko
Duration: Approx. 44 hours to complete
Description: You will learn about data preprocessing in Python and R, Linear Regression, Polynomial Regression, Support Vector Regression, Decision Tree Regression, Random Forest Regression, Evaluation Regression Model Performance, Regression Model Selection, Logistic Regression, KNN, SVM, Naive Bayes, K-Means Clustering, Hierarchical Clustering, Association Rule Learning, Apriori, Reindorcemenr Learning, Natural Language Processing, Dimensionality Reduction, PCA, LDA, Model Selection and Boosting.
Prerequisite: Basics of Python programming would be helpful.
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