– What is Artificial Intelligence
– Machine Learning & Types
– Fundamentals of Python
– Data Preprocessing in python
– Defining a Model
– Error Calculation
– Gradient Descent Algorithm

Problem: Predicting Housing Prices based on the size of the house using Gradient Descent Algorithm

– Classification problem
– Data Preprocessing
– Defining a Model
– One vs. All
– Error & Accuracy Calculation
– Gradient Descent Algorithm
– Prediction

Problem: Handwritten Digit Recognition using Gradient Descent Algorithm

– Introduction to Scikit Learn
– Label Encoding
– Data Preprocessing
– Gradient Descent Algorithm, TNC
– Regularization Parameter
– Hyperparameter Grid Search
– Bias, Variance, Accuracy, Precision

Problem: Solve Kaggle Datasets

– What is KNN?
– Example KNN Problem
– Defining the Objective function
– Optimize Objective function
– Prediction & Accuracy

Problem: Online shoppers’ buying intention.

– What is Decision Tree?
– Calculating Entropy
– Calculating Information gain
– Gini Index
– Objective Function

– What is Random Forest & Bagging?
– Advantages of using Random Forest
– Pruning
– Objective Function
– Prediction & Accuracy

Decision Tree Problem: Depending on the weather predicting the possibility of playing cricket
Random Forest Problem: Behavioral Risk factor Surveillance System

– NLP Basics
– N Gram Model, Bag of Words
– TF-IDF Vectorisation
– Bayes Theorem
– Multinomial & Bernoulli Naive Bayes
– SMOTE
– Prediction & Accuracy

Problem: Building a spam classifier