TASK 1 - TITANIC SURVIVAL PREDICTION(Week-1)

Beginner

* Use the Titanic dataset to build a model that predicts whether a passenger on the Titanic survived or not. This is a classic beginner project with readily available data.

* The dataset typically used for this project contains information about individual passengers, such as their age, gender, ticket class, fare, cabin, and whether or not they survived.

TASK 2 - IRIS FLOWER CLASSIFICATION(Week-2)

Intermediate

* The Iris flower dataset consists of three species: setosa, versicolor,and virginica. These species can be distinguished based on their measurements. Now, imagine that you have the measurements of Iris flowers categorized by their respective species. Your objective is to train a machine learning model that can learn from these measurements and accurately classify the Iris flowers into their respective species.

* Use the Iris dataset to develop a model that can classify iris flowers into different species based on their sepal and petal measurements. This dataset is widely used for introductory classification tasks.

TASK 3 - CREDIT CARD FRAUD DETECTION(Week-3)

Advanced

* Build a machine learning model to identify fraudulent credit card transactions.

* Preprocess and normalize the transaction data, handle class imbalance issues, and split the dataset into training and testing sets.

* Train a classification algorithm, such as logistic regression or random forests, to classify transactions as fraudulent or genuine.