ankitchandola Goto Github PK

amazon-clone

ankitchandola

A little about myself

best-readme-template

An awesome README template to jumpstart your projects!

bookstore

bootstrap4-project

box-office

chat-app

churn-model-prediction

Employee churn can be defined as a leak or departure of an intellectual asset from a company or organization. Alternatively, in simple words, you can say, when employees leave the organization is known as churn. Another definition can be when a member of a population leaves a population, is known as churn. In Research, it was found that employee churn will be affected by age, tenure, pay, job satisfaction, salary, working conditions, growth potential and employee’s perceptions of fairness. Some other variables such as age, gender, ethnicity, education, and marital status, were essential factors in the prediction of employee churn. In some cases such as the employee with niche skills are harder to replace. It affects the ongoing work and productivity of existing employees. Acquiring new employees as a replacement has its costs such as hiring costs and training costs. Also, the new employee will take time to learn skills at the similar level of technical or business expertise knowledge of an older employee. Organizations tackle this problem by applying machine learning techniques to predict employee churn, which helps them in taking necessary actions.

credit-card-fraud-detection

Throughout the financial sector, machine learning algorithms are being developed to detect fraudulent transactions. In this project, that is exactly what we are going to be doing as well. Using a dataset of of nearly 28,500 credit card transactions and multiple unsupervised anomaly detection algorithms, we are going to identify transactions with a high probability of being credit card fraud. In this project, we will build and deploy the following two machine learning algorithms: Local Outlier Factor (LOF) Isolation Forest Algorithm Furthermore, using metrics suchs as precision, recall, and F1-scores, we will investigate why the classification accuracy for these algorithms can be misleading.

dsa-lvl1-getting-started

dsa-lvl1-patterns

ecommerce-react

eCommerce web application using React, Redux, Redux-Saga, Firebase and SASS.

hoic-assignment-client

hoic-assignment-server

instagram-clone

mini-mern-ecommerce-project

React & Redux - NodeJS & ExpressJS & MongoDB.. Basic Shopping Cart Functionality

ml-spam-sms-classification

Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification

part-2-major-lstm

rinem

stageappmock

mock app for stage

tic-tac-toe

trainingtask