Regression, Perceptron Algorithms, Decision Trees, Naive Bayes, Support Vector Machines, Ensemble of Learners, Evaluation Metrics, Training and Tuning Models, Introduction to Neural Networks, Implementing Gradient Descent, Training Neural Networks, Deep Learning with TensorFlow, Clustering, Hierarchical and Density-Based Clustering, Gaussian Mixture Models, Dimensionality Reduction, Facial Expression Recognition, Flower Classification…