venkatesh-eranti Goto Github PK

classification_milestone_project

Predicting Heart Disease using Machine Learning

clustering_bank-telemarketing-campaign-case-study

In this case study I will be doing Exploratory Data Analytics with the help of a case study on Bank marketing campaign.

clustering_cricket-data

Analyze the data of batting figures of batsmen in ODI matches by Choosing strike rate and average as the two factors on which clustering the data

clustering_milestone-project-wholesale-customers

The wholesale distributor is considering changing its delivery service from currently 5 days a week to 3 days a week. However, the distributor will only make this change in delivery service for customers that react positively. How can the wholesale distributor use the customer segments to determine which customers, if any, would reach positively to the change in delivery service?

clustering_project_online-retail_case-study

For an UK based non-store online retail for which we need to cluster it's customers in to different groups so that we can run targeted campaign for each group

covid_tracker

covid_tracker from covid19india.org

dbscan-vs-k-means-vs-hierarchical-clustering

K-Means and Hierarchical Clustering both fail in creating clusters of arbitrary shapes. They are not able to form clusters based on varying densities. That’s why we need DBSCAN clustering.

decision_tree-regressor

Boston Housing Price prediction and comparison of evaluation metrics by using Decision tree regressor algorithm and tuning parameters by using GridSearchCV (with different parameters like Criterion, Max depth, min samples split and min samples leaf ...)

housing_case-study

A real estate company that has a dataset containing the prices of properties in the Delhi region. It wishes to use the data to optimise the sale prices of the properties based on important factors such as area, bedrooms, parking, etc

media_company_case_study

A digital media company (similar to Voot, Hotstar, Netflix, etc.) had launched a show. Initially, the show got a good response, but then witnessed a decline in viewership. The company wants to figure out what went wrong

mnist_pca

The MNIST database of handwritten digits, available from (http://yann.lecun.com/exdb/mnist/), has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image.<br> It is a good database for people who want to try learning techniques and pattern recognition methods on real-world data while spending minimal efforts on preprocessing and formatting.

myntra_sales_case-study

myntra_sales_case-study

random_forest_regressor

building a ML algorithm to predict house prices for Boston dataset by using ML map from sklearn

simple_linear_regression

building a simple linear regression model in Python using the advertising dataset by using both Sklearn and Statsmodels and comapare coefficient and intercepts for both models

stackoverflow_2020_survey

In February 2020 nearly 65,000 developers told stackoverflow that how they learn and level up, which tools they’re using, and what they want.

svr_support_vector_regression

Boston Housing Price prediction and comparison of evaluation metrics with Support Vector Regression and GridSearchCV (with different kernels and parameters like C and epsilon) and Multiple Linear Regression

telecom_churn_nochurn

trivial_algos