Level 3 AIML

Task 1 - Decision Tree based ID3 Algorithm

Understanding Basic Terminology
Understand ID3
Implement ID3 for ID3

Here is my Task ID3

Task 2 - Naive Bayesian Classifier

Understand Naive Bayesian Classifier, watch it in action using sklearn
Implement Naive Bayesian Classifier for text classification and other applicable datasets

Here is my Task Naive Bayesian Classifier

Task 3 - Ensemble techniques

What are ensemble techniques??
Apply the ensemble techniques on the Titanic Dataset

Here is my Task Ensemble techniques

Task 4 - Random Forest, GBM and Xgboost

Random forest: Understand & Implement
GBM: Understand & Implement
Xboost: Understand & Implement

Here is my Task Random Forest, GBM and Xgboost

Task 5 - Hyperparameter Tuning

Understanding
Pick a suitable problem (and dataset) and train a model to fit the problem
Tune the hyperparameters of the model to increase accuracy

Here is my task Hyperparameter Tuning

Task 6 : Image Classification using KMeans Clustering

Understanding K Means Clustering:
Classify a given set of images into a given number of categories using KMeans Clustering using MNIST dataset

Here is my task Image Classification using KMeans Clustering