🎯 Task-1-Prediction-using-Supervised-Learning Here I have created the prediction using simple linear regression where I have predicted the marks of a student based on the number of study hours of that student.
Predict the percentage of an student based on the no. of study hours.
● This is a simple linear regression task as it involves just 2 variables.
● You can use R, Python, SAS Enterprise Miner or any other tool
● Data can be found at http://bit.ly/w-data
● What will be predicted score if a student studies for 9.25 hrs/ day?
🎯 Task-2-Prediction-using-Unsupervised-ML Here I have created the prediction model using the Unsupervised ML and I have predicted the model using the K means Clustering
From the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.
● Use R or Python or perform this task
● Dataset : https://bit.ly/3kXTdox
🎯 Task-3-Exploratory-Data-Analysis-Retail Here I have created the analysis model of a Super market datasheet given by the company and have deployed the parameters successfully.
Perform ‘Exploratory Data Analysis’ on dataset ‘SampleSuperstore’
● As a business manager, try to find out the weak areas where you can work to make more profit.
● What all business problems you can derive by exploring the data?
● You can choose any of the tool of your choice (Python/R/Tableau/PowerBI/Excel/SAP/SAS)
● Dataset: https://bit.ly/3i4rbWl
🎯 Task-4-Exploratory-Data-Analysis-Terrorism Here in this project I have analysed the huge dataset of Terrorism where all the details are being provided
Exploratory Data Analysis - Terrorism
(Level - Intermediate)
● Perform ‘Exploratory Data Analysis’ on dataset ‘Global Terrorism’
● As a security/defense analyst, try to find out the hot zone of terrorism.
● What all security issues and insights you can derive by EDA?
● You can choose any of the tool of your choice
(Python/R/Tableau/PowerBI/Excel/SAP/SAS)
● Dataset: https://bit.ly/2TK5Xn5
🎯 Task 5 - Prediction-using-Decision-Tree-Algorithm Prediction using Decision Tree Algorithm of the iris dataset
● Create the Decision Tree classifier and visualize it graphically.
● The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.
● Dataset : https://bit.ly/3kXTdox
🎯 Task-6-Stock-Market-Prediction Here I have created the model of Stock Market Prediction using the TensorFlow Modelling
Objective: Create a hybrid model for stock price/performance prediction using numerical analysis of historical stock prices, and sentimental analysis of news headlines
● Stock to analyze and predict - SENSEX (S&P BSE SENSEX)
● Download historical stock prices from finance.yahoo.com
● Download textual (news) data from https://bit.ly/36fFPI6
● Use either R or Python, or both for separate analysis and then combine the findings to create a hybrid model
● You are free to select a different stock to analyze and news dataset as well while not changing the objective of the task.