The course covers Machine Learning in exhaustive way. The presentations and hands-on practical are made such that it’s made easy. The knowledge gained through this tutorial series can be applied to various real world scenarios.

UnSupervised Learning and Supervised Learning are dealt in-detail with lots of bonus topics.

The course contents are given below:

• Introduction to Machine Learning
• Introductions to Deep Learning
• Installations
• Unsupervised Learning
• Clustering, Association
• Agglomerative, Hands-on
• DBSCAN, Hands-on
• Mean Shift, Hands-on
• K Means, Hands-on
• Association Rules, Hands-on
• (PCA: Principal Component Analysis)
• Supervised Learning
• Regression, Classification
• Train Test Split, Hands-on
• k Nearest Neighbors, Hands-on
• kNN Algo Implementation
• Support Vector Machine (SVM), Hands-on
• Support Vector Regression (SVR), Hands-on
• SVM (non linear svm params), Hands-on
• SVM kernel trick, Hands-on
• SVM mathematics
• Linear Regression, Hands-on
• Gradient Descent overview
• One Hot Encoding (Dummy vars)
• One Hot Encoding with Linear Regr, Hands-on
• Info about Datasets