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-machine-learning-slides

Slides for CMU 10601, 10605

06-623-mathematical-modelling-of-chemical-engineering-processes

Work done for the course 'Mathematical Modelling of Chemical Engineering Processes', all of the work is in MATLAB

100-days-of-ml-code

100 Days of ML Coding

10601-18fall-homework

My homework solutions for CMU Machine Learning Course (10-601 2018Fall)

2016-ml-contest

Machine learning contest - October 2016 TLE

2019-03-27-purdue

Purdue University workshop, March 2019

2020-fairhurst-hydrogen-production

This repository holds data analysis of the hydrogen required by the UI fleet and MTD fleet to become carbon free.

2d-navier-stokes-finite-difference-solver

This project used the forward and backward difference schemes for coding the solution of partial differential equations like linear and non linear convection, diffusion, burger's equation, laplace and navier-stokes equation to simulate the physical phenomena depicted by them.

a-predictive-analytics-model-to-classify-bankruptcy-for-a-firm

The objective of the project was to develop a predictive model that combines various econometric measures to foresee a financial condition (Bankruptcy or not) of a firm based on a financial balance sheet data set available on Kaggle. This was done as part of the Data Mining course at the Krannert Business Analytics Program, Purdue University - Team: Zaid Ahmed, Mohinder Goyal and Maharshi Dutta

adsorption

All the adsorption process related

advanced-chemical-reaction-engineering

advanced-data-analytics

Advanced Data Analytics for Chemical Engineers

advanced_machine_learning

Projects from the 252-0535-00L Advanced Machine Learning at ETH Zürich Fall Semester 2019

advanced_process_control

Endothermic Reactor Modeling with Matlab

ai-materials

Various models used to train a machine learning model to predict viable metal-hydride based hydrogen compressors.

ammonia-synthesis-simulation

Code I wrote which simulates an ammonia synthesis reactor by solving ODE system for flow, shell&tube heat transfer, pressure, and chemical kinetics

ammoniareactormodel

Effectiveness factor in progress

an-introduction-to-machine-intelligence

Repository containing Jupyter notebooks for the course: An Introduction to Machine Intelligence for Architects and other Nonengineers ETH Zurich, Chair for CAAD, Autumn semester 2019

anaerobic_digester

BMI Hydraulics Project on Anaerobic Digester

anaerobicdigestion

The purpose of this app is to optimize the model parameters in order to increase the profitability of the bioreactor. The user will be able to adjust initial bacteria concentrations, reactor temperature (both static and dynamic), etc., and see a visual representation of the outcome. Note that not all adjustable parameters will have an effect on every plot. As soon as the user loads the app, the model is compiled and run using the current parameter settings. As the user adjusts these parameters, the plots and tables will update according to the new settings once the "Re-simulate" button has been clicked (This button is on each of the table and plot tabs). The tabs on the left then allow the user to navigate the simulated reactor output and read more about the process. You can also specify the time in which to truncate the data and evaluate the output, though the minimum value is currently 100 h. The reactor that follows the anaerobic digestor is capable of removing small quantities left over. Ideally you would set a minimum acceptable concentration, and optimize parameters to decrease the time required to reduce the contaminants to that concentration, though this not been implemented due to the lack of observational data.

analysis-and-process-simulation

Full stack Java Application that cuts costs of creation, invoice management and process simulation associated with setting up pilot water purification plants.

applied-machine-learning

Applied Machine Learning @ http://amitkaps.com/ml

ar-tools

A set of utility functions and Jupyter notebooks for attainable region (AR) computations.

artificial-intelligence-by-example

Artificial Intelligence By Example, published by Packt

ashrae_energy_predictor

Kaggle competition of ASHRAE_Energy_Predictor, use brillent machine learning models and won 8th from 3595 teams

aspen

Projects on Aspen Plus and AspenHYSYS

aspen-optimization-nsga2

Optimization of a chemical reactor using Aspen Plus, python and the NSGA2 algorithm

aspen-plus-pso-ga-pyrolysis

atlantis

A browser based interface for the Open Source Energy Modelling System model (OSeMOSYS), the Model Management Infrastructure (MoManI) provides tools to construct energy models, explore scenarios and visualize results.

automated-feature-engineering

Automated feature engineering in Python with Featuretools