What you’ll learn
- Fundamental of Machine Learning; Introduction, types of machine learning, applications
- Supervised, Unsupervised and Reinforcement learning
- Principal Component Analysis (PCA); Introduction, mathematical and graphical concepts
- Confusion matrix, Under-fitting and Over-fitting, classification and regression of machine model
- Support Vector Machine (SVM) Classifier; Introduction, linear and non-linear SVM model, optimal hyperplane, kernel trick, project in Python
- K-Nearest Neighbors (KNN) Classifier; Introduction, k-value, Euclidean and Manhattan distances, outliers, project in Python
- Naive Bayes Classifier; Introduction, Bayes rule, project in Python
- Logistic Regression Classifier; Introduction, non-linear logistic regression, sigmoid function, project in Python
- Decision Tree Classifier; Introduction, project in Python
How to Enroll Machine Learning for Beginner course?
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