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airbnb_pricingmodel

awscodedeploy

cars4u_linearregression

Background & Context There is a huge demand for used cars in the Indian Market today. As sales of new cars have slowed down in the recent past, the pre-owned car market has continued to grow over the past years and is larger than the new car market now. Cars4U is a budding tech start-up that aims to find footholes in this market.

computervision

The Aarhus University Signal Processing group, in collaboration with University of Southern Denmark, has recently released a dataset containing images of unique plants belonging to 12 species at several growth stages. There is dataset of images of plant seedlings at various stages of grown. Each image has a filename that is its unique id. The dataset comprises 12 plant species. The goal of the project is to create a classifier capable of determining a plant's species from a photo.

coursera-test

Coursera Test Repository

jenkins-test

jupyter_access-

Connect with your personal system to remote server (with/without jump server) for highly intensive computation Machine Learning Model

lifeexpectancy_influencingfactors

Context: There have been a lot of studies undertaken in the past, on factors affecting life expectancy, considering demographic variables, income composition, and mortality rates. It was found that the effect of immunization and human development index was not taken into account in the past. Important immunization like Hepatitis B, Polio, and Diphtheria will also be considered. In a nutshell, this case study will focus on immunization factors, mortality factors, economic factors, social factors, and other health-related factors as well. In this case study, we will use linear regression to see the effect of various factors on Life Expectancy

lockdownanalysis

lwprojgithub

movielens_data_analysis-

Project - MovieLens Data Analysis The GroupLens Research Project is a research group in the Department of Computer Science and Engineering at the University of Minnesota. The data is widely used for collaborative filtering and other filtering solutions. However, we will be using this data to act as a means to demonstrate our skill in using Python to “play” with data.

neuralnet

The case study is from an open-source dataset from Kaggle. The dataset contains 10,000 sample points with 14 distinct features such as CustomerId, CreditScore, Geography, Gender, Age, Tenure, Balance, etc.

personal-loan-campaign-modelling

To build a model that will help the marketing department to identify the potential customers who have a higher probability of purchasing the loan. To explore ways of converting its liability customers to personal loan customers (while retaining them as depositors) Expanding the asset customer base rapidly to bring in more loan business and in the process, earn more through the interest on loans To predict whether a liability customer will buy a personal loan or not and further to find the significance of different parameters.

pima-indians-diabetes-analysis

Logistic regression (correction) to model the "Pima Indians Diabetes" data set. This model will predict which people are likely to develop diabetes. 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. Data Dictionary: Preg: Number of times pregnant Plas: glucose concentration a 2 hours in an oral glucose tolerance test Pres: blood pressure (mm Hg) Skin: skin fold thickness (mm) test: 2-Hour serum insulin (mu U/ml) mass: BMI (weight in kg/(height in m)^2) pedi: pedigree function age: Age (years) Class: variable (0 or 1) 268 of 768 are 1, the others are 0

simple-java-maven-app

For an introductory tutorial on how to use Jenkins to build a simple Java application with Maven.

unsupervisedlearning

AllLife Bank wants to focus on its credit card customer base in the next financial year. They have been advised by their marketing research team, that the penetration in the market can be improved. Based on this input, the Marketing team proposes to run personalised campaigns to target new customers as well as upsell to existing customers. Another insight from the market research was that the customers perceive the support services of the bank poorly. Based on this, the Operations team wants to upgrade the service delivery model, to ensure that customers queries are resolved faster.