harpreetsd99

Automobile_Dataset

This data set consists of three types of entities: (a) the specification of an auto in terms of various characteristics, (b) its assigned insurance risk rating, (c) its normalized losses in use as compared to other cars. The second rating corresponds to the degree to which the auto is more risky than its price indicates. Cars are initially assigned a risk factor symbol associated with its price. Then, if it is more risky (or less), this symbol is adjusted by moving it up (or down) the scale. Actuarians call this process "symboling". A value of +3 indicates that the auto is risky, -3 that it is probably pretty safe. The third factor is the relative average loss payment per insured vehicle year. This value is normalized for all autos within a particular size classification (two-door small, station wagons, sports/speciality, etc…), and represents the average loss per car per year. Note: Several of the attributes in the database could be used as a "class" attribute.

Big-Data-Analysis-on-Healthcare-Data-by-CMS

The comprehensive methodology, rooted in data integration, feature engineering, and advanced analytics, has yielded a powerful model capable of identifying deceptive patterns and potential fraud instances.

Brand-Monitoring-System-using-Sentimental-Analysis-with-Python-MySQL-and-Twitter-API

Brand Monitoring System using Sentimental Analysis with Python, MySQL, and Twitter API

Case-Study---How-Does-a-Bike-Share-Navigate-Speedy-Success-

In this case study, you will perform many real-world tasks of a junior data analyst. You will work for a fictional company, Cyclistic, and meet different characters and team members. In order to answer the key business questions, you will follow the steps of the data analysis process

Hotel-Cancelation

The dataset contains 119390 observations for a City Hotel and a Resort Hotel. Each observation represents a hotel booking between the 1st of July 2015 and 31st of August 2017, including booking that effectively arrived and booking that were canceled

HR-Data-Analysis-using-SQL-and-PowerBI

Using SQL and PowerBI creating a Human Resource data analysis.

Policy-Recommendation-using-Real-World-Data

Using real-world-data creating a model to recommend real policies to the individuals for better political campaigns

Tableau-Dashboard---Pizza-Franchise-Sales

Tableau dashboard using MySQL for Pizza Franchise Sales with 45k+ rows w.r.to different KPI's and Problem statement.

Wildfire-Prevention

Participated in Data Hackathon to understand different causes and way to prevent wildfire in Canada

harpreetsd99/Automobile_Dataset

This data set consists of three types of entities: (a) the specification of an auto in terms of various characteristics, (b) its assigned insurance risk rating, (c) its normalized losses in use as compared to other cars. The second rating corresponds to the degree to which the auto is more risky than its price indicates. Cars are initially assigned a risk factor symbol associated with its price. Then, if it is more risky (or less), this symbol is adjusted by moving it up (or down) the scale. Actuarians call this process "symboling". A value of +3 indicates that the auto is risky, -3 that it is probably pretty safe. The third factor is the relative average loss payment per insured vehicle year. This value is normalized for all autos within a particular size classification (two-door small, station wagons, sports/speciality, etc…), and represents the average loss per car per year. Note: Several of the attributes in the database could be used as a "class" attribute.

harpreetsd99/Big-Data-Analysis-on-Healthcare-Data-by-CMS

The comprehensive methodology, rooted in data integration, feature engineering, and advanced analytics, has yielded a powerful model capable of identifying deceptive patterns and potential fraud instances.

harpreetsd99/Brand-Monitoring-System-using-Sentimental-Analysis-with-Python-MySQL-and-Twitter-API

Brand Monitoring System using Sentimental Analysis with Python, MySQL, and Twitter API

harpreetsd99/Case-Study---How-Does-a-Bike-Share-Navigate-Speedy-Success-

In this case study, you will perform many real-world tasks of a junior data analyst. You will work for a fictional company, Cyclistic, and meet different characters and team members. In order to answer the key business questions, you will follow the steps of the data analysis process

harpreetsd99/Hotel-Cancelation

The dataset contains 119390 observations for a City Hotel and a Resort Hotel. Each observation represents a hotel booking between the 1st of July 2015 and 31st of August 2017, including booking that effectively arrived and booking that were canceled

harpreetsd99/HR-Data-Analysis-using-SQL-and-PowerBI

Using SQL and PowerBI creating a Human Resource data analysis.

harpreetsd99/Policy-Recommendation-using-Real-World-Data

Using real-world-data creating a model to recommend real policies to the individuals for better political campaigns

harpreetsd99/Tableau-Dashboard---Pizza-Franchise-Sales

Tableau dashboard using MySQL for Pizza Franchise Sales with 45k+ rows w.r.to different KPI's and Problem statement.

harpreetsd99/Wildfire-Prevention

Participated in Data Hackathon to understand different causes and way to prevent wildfire in Canada

harpreetsd99/Amazon-Reiews

Using NLP, creating model to understand reviews of the customers using amazon reiews

harpreetsd99/ANZ-Virtual_Internship

Data@ANZ is about mining and linking datasets to develop stories that matter and challenge the status quo, to deliver on ANZ’s purpose “to shape a world where people and communities thrive”. Our data people love to explore opportunities, innovate, be challenged and transform their ideas, and have created this experience to give you a taste of some of the challenging problems they love to tackle.

harpreetsd99/ASCEND

Development of a web app using Flask and built a data pipeline for ASCEND, processing data from 15,000+ users to provide insights for enhancing immigrants transitioning into the Canadian job market. Conducted data wrangling and transformation, translated 10,000+ French responses into English, and created Power BI dashboards showcasing KPIs

harpreetsd99/car-services

Car Service Management System

harpreetsd99/CardioGoodFitness_Dataset

The market research team at AdRight is assigned the task to identify the profile of the typical customer for each treadmill product offered by CardioGood Fitness. The market research team decides to investigate whether there are differences across the product lines with respect to customer characteristics. The team decides to collect data on individuals who purchased a treadmill at a CardioGoodFitness retail store during the prior three months. The data are stored in the CardioGoodFitness.csv file. The team identifies the following customer variables to study: product purchased, TM195, TM498, or TM798; gender; age, in years;education, in years; relationship status, single or partnered; annual household income ($); average number of times the customer plans to use the treadmill each week; average number of miles the customer expects to walk/run each week; and self-rated fitness on an 1-to-5 scale, where 1 is poor shape and 5 is excellent shape. Perform descriptive analytics to create a customer profile for each CardioGood Fitness treadmill product line.

harpreetsd99/Complete-Python-3-Bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

harpreetsd99/CrowNest-YVR_Hackthon

Task is to develop a solution that builds off the Crow's Nest concept, utilizing cutting-edge technologies such as intelligent sensors, computer vision, and machine learning to monitor, detect, and report real-time insights into the condition of public spaces.

harpreetsd99/Data-Analytics-in-Finance-Sector-

harpreetsd99/data-science-complete-tutorial

For extensive instructor led learning

harpreetsd99/data-structures-algorithms-python

This tutorial playlist covers data structures and algorithms in python. Every tutorial has theory behind data structure or an algorithm, BIG O Complexity analysis and exercises that you can practice on.

harpreetsd99/Deployment-flask

harpreetsd99/Diabetes_Dataset

This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset. Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage. Content The datasets consists of several medical predictor variables and one target variable, Outcome. Predictor variables includes the number of pregnancies the patient has had, their BMI, insulin level, age, and so on. Can you build a machine learning model to accurately predict whether or not the patients in the dataset have diabetes or not?

harpreetsd99/harpreetsd99.github.io

harpreetsd99/InfyTQ-Answers

Solution of all InfyTQ Assignments, Exercise, Quiz

harpreetsd99/Internship_Codellion

Internship As Web Developer for making an website known as frood

harpreetsd99/Kashish-Jain-KJ.github.io

harpreetsd99/OpenCV-Projects

A collection of programs, that consists of the most primitive and simple, yet some of the most crucial elements of image processing using OpenCV. This was created while experimenting with and learning OpenCV as a result of being inspired by the "Digital Signal & Image Processing" subject in my final academic year.

harpreetsd99/Sentimental-Analysis

A real-time interactive web app based on data pipelines using streaming Twitter data, automated sentiment analysis, and MySQL&PostgreSQL database (Deployed on Heroku)

harpreetsd99/Spark-for-Big-Data-using-PySpark

Practicing Spark for Big Data

harpreetsd99/SQLite3

Trying sqlite3 for connecting sql with python and using python pandas for analysis and seaborn for visualization

harpreetsd99/YouTube-Indian-trending-video-analysis

Data-Science project in Python