🌍 Python package of VTK-based algorithms to analyze geoscientific data and models

A collaborative list of awesome CryoEM (Cryo Electron Microscopy) resources.

Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.

Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Mo…

Worked on Real Estate Price data analysis by scraping website from www.99acres.com to help the housing domain as well as estimate the sale value of various houses and open plots.

Data: Boston Housing Dataset (HousingData.csv) Programming language(s): R Tool(s): RStudio Business problem: To understand the drivers behind the value of houses in Boston and provide data-driven recommendation to the client on how they can increase the value of housing.The Boston housing dataset consisted of 506 observations and 14 variables. P…

PyR@TE 3

The goal of this project is to build an RL-based algorithm that can help cab drivers maximize their profits by improving their decision-making process on the field. Taking long-term profit as the goal, a method is proposed based on reinforcement learning to optimize taxi driving strategies for profit maximization. This optimization problem is fo…

Tool demonstrating building credit risk models

This project focuses on using the AWS open-source AutoML library, AutoGluon, to predict bike sharing demand using the Kaggle Bike Sharing demand dataset.

Runtime EntityFramework model builder from metadata tables. Provides a static usage at compile time via proxies classes. Created as CRM/ERP core.

Jupyter Notebooks for visualizing and exploring empirical model building. http://charlesreid1.github.io/empirical-model-building

The fraud identification models were build using Python Scikit-learn machine-learning module.

Stochastic gradient descent with model building

In this project, I predict which customers are more likely to respond positively to a bank marketing call by setting up a regular savings deposit or subscribing the term “made_deposit”. Three classification algorithms have been developed in order to predict the target variable. Logistic Regression, Decision Tree and Multi-Layer Perceptron (MLP).…

The goal of this project is to build multiple linear regression models for the prediction of car prices.

Explore basic machine learning algorithms and learn to build, train, and evaluate Artificial Neural Networks in Keras.

This project consists of custom built modelling frameworks for pricing equity assets. Through the project's evolution, the framework evolves from a single case Discounted Cash Flow model to an interactive Probability Weighted Discounted Cash Flow model that includes multiple cases, multiple supporting models and is all built in Excel while utili…

Competition conducted by American Express on HackerEarth Platform to Predict Credit Card Defaulters by building Machine Learning Models for the given data.