EDA on iris dataset

Access an open source dataset “Titanic”. Apply pre-processing techniques onthe raw dataset.

Build training and testing dataset of assignment 1 to predict the probability of a survival of a person based on gender, age and passenger-class.

Load the data from data file and split it into training and test datasets. Summarize the properties in the training dataset. The number of rings is the value to predict: either as a continuous value or as a classification problem. Predict the age of abalone from physical measurements using linear regression or predict ring class as classification problem

Use the dataset in assignment 4 (Abalone dataset).

a) Load the data from data file

b) Explore the shape of dataset

c) Summarize the properties in the training dataset. Write findings from column description.

d) Check the dataset for any missing values, impute the missing values and also print out the correlation matrix.

e) Split data into train, test sets

f) Predict ring class as classification problem using Naive Bayes and Decision Tree Classifier

g) Calculate the accuracy score of the two models for both training and test data set.

h) Display confusion matrix

i) Display the classification report

j) Compare the two models based on accuracy score and classification report and give your reasoning on which is the best model in this case.

Use Netflix Movies and TV Shows dataset from Kaggle and perform following operation :

1.Make a visualization showing the total number of movies watched by children

2.Make a visualization showing the total number of standup comedies

3.Make a visualization showing most watched shows.

4.Make a visualization showing highest rated showMake a dashboard (DASHBOARD A) containing all of these above visualizations.