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100-days-of-ml-code

A day to day plan for this challenge. Covers both theoritical and practical aspects

credit_card_fraud_detection

Credit card fraud is any dishonest act or behavior to obtain information without the proper authorization of the account holder for financial gain. Among the different ways of committing fraud, skimming is the most common one. Skimming is a method used for duplicating information located on the magnetic stripe of the card.

credit_eda-case-study

Exploratory Data Analysis for Credit Loan dataset

eda----exploratory-data-analysis

EDA - Exploratory Data Analysis using python

hive_case_study

Problem Statement With online sales gaining popularity, tech companies are exploring ways to improve their sales by analysing customer behaviour and gaining insights about product trends. Furthermore, the websites make it easier for customers to find the products they require without much scavenging. Needless to say, the role of big data analysts is among the most sought-after job profiles of this decade. Therefore, as part of this assignment, we will be challenging you, as a big data analyst, to extract data and gather insights from a real-life data set of an e-commerce company.

imdb-movie-data-visualisation-assignment

IMDb Movie Data Visualisation Assignment using #python3, including #EDA, #pandas, #numpy, #datavisualization, #matplotlib

lead_scoring_case_study_logistic_regression

Problem Statement An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses. The company markets its courses on several websites and search engines like Google. Once these people land on the website, they might browse the courses or fill up a form for the course or watch some videos. When these people fill up a form providing their email address or phone number, they are classified to be a lead. Moreover, the company also gets leads through past referrals. Once these leads are acquired, employees from the sales team start making calls, writing emails, etc. Through this process, some of the leads get converted while most do not. The typical lead conversion rate at X education is around 30%. Now, although X Education gets a lot of leads, its lead conversion rate is very poor. For example, if, say, they acquire 100 leads in a day, only about 30 of them are converted. To make this process more efficient, the company wishes to identify the most potential leads, also known as ‘Hot Leads’. If they successfully identify this set of leads, the lead conversion rate should go up as the sales team will now be focusing more on communicating with the potential leads rather than making calls to everyone. A typical lead conversion process can be represented using the following funnel: Lead Conversion Process - Demonstrated as a funnel

linear-regression

Univariate LinearRegression HousingPrice

linear_regression

Linear regression Example Demo for Workshop

linear_regression_bike_sharing_assignment_upgrad

Linear_Regression_Bike_Sharing_Assignment

logistic-regression

Logistic Regression

resume

resume.IO

rsvp-movies-analysis

RSVP Movies is an Indian film production company which has produced many super-hit movies. They have usually released movies for the Indian audience but for their next project, they are planning to release a movie for the global audience in 2022. The production company wants to plan their every move analytically based on data and have approached you for help with this new project. You have been provided with the data of the movies that have been released in the past three years. You have to analyse the data set and draw meaningful insights that can help them start their new project.

saikatchowdhury.github.io

spoon-knife

This repo is for demonstration purposes only.

tableau_work_dashboard_story

Creating Tableau Dashboard and analysis using Sample+Superstore+(Modified) data

upgrad_clustering_assignment

Clustering_Assignmeent -- HELP International is an international humanitarian NGO that is committed to fighting poverty and providing the people of backward countries with basic amenities and relief during the time of disasters and natural calamities. It runs a lot of operational projects from time to time along with advocacy drives to raise awareness as well as for funding purposes.

webscraping

work-shop-1-documentation

Documentation for Work Shop -1 by PappuGroup

workshop_one

Workshop One Details