Introduction- What Is Human Learning?- Types Of Human Learning. What Is Machine Learning?- Types Of Machine Learning: Supervised Learning- Unsupervised Learning- Reinforcement Learning- Comparison – Supervised, Unsupervised, And Reinforcement Learning- Applications Of Machine Learning: Banking And Finance- Insurance- Healthcare.

Machine Learning Activities- Basic Types Of Data In Machine Learning- Exploring Structure Of Data: Exploring Numerical Data- Plotting And Exploring Numerical Data- Exploring Categorical Data- Exploring Relationship Between Variables. Data Quality And Remediation: Data Quality- Data Remediation. Data Pre-Processing: Dimensionality Reduction- Feature Subset Selection.

Selecting A Model: Predictive Models- Descriptive Models. Training A Model: Holdout Method- K-Fold Cross-Validation Method- Bootstrap Sampling- Lazy Vs. Eager Learner. Model Representation And Interpretability: Underfitting- Overfitting- Bias – Variance Trade-Off. 3.5 Evaluating Performance Of A Model: Supervised Learning – Classification- Supervised Learning – Regression- Unsupervised Learning - Clustering -Improving Performance of a Model.

What Is A Feature?- What Is Feature Engineering?- Feature Transformation: Feature Construction- Feature Extraction. Feature Subset Selection: Feature Construction- Feature Extraction- Feature Subset Selection: Issues In High-Dimensional Data- Key Drivers Of Feature Selection – Feature Relevance And Redundancy- Measures Of Feature Relevance And Redundancy- Overall Feature Selection Process.

Representation Learning: Supervised Neural Networks And Multilayer Perceptron- Independent Component Analysis (Unsupervised)- Autoencoders- Various Forms Of Clustering- Active Learning: Heuristics For Active Learning- Active Learning Query Strategies- Instance-Based Learning (Memory-Based Learning): Radial Basis Function- Pros And Cons Of Instance-Based Learning Method. Association Rule Learning Algorithm: Apriori Algorithm- Eclat Algorithm- Ensemble Learning Algorithm: Bootstrap Aggregation (Bagging)- Boosting- Gradient Boosting Machines (Gbm).