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pysca

Python Libraries for Performing Statistical Coupling Analyses of Protein Sequence Alignments

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If you would like to contribute to this project, contact Kevin Dalton at [email protected] or Alexandre Colavin at [email protected]

pysca's Projects

ai_supply_chain icon ai_supply_chain

This is the code for "AI for Supply Chain" by Siraj Raval on Youtube

cvrptw icon cvrptw

Capacitated Vehicle Routing Problem with Time Windows (NP-Hard). Winner at ICHack 18.

deeptravel icon deeptravel

:car: Solving Traveling Salesman Problem (TSP) using Deep Learning

dynamic-pricing icon dynamic-pricing

This machine learning model (deep and wide learning model) helps us to implement dynamic pricing feature of a supply chain business problem. This model uses tensorflow to solve the problem and can be structured accordingly to run efficiently on Google Cloud Platform.

flash_breach icon flash_breach

Solution to vehicle routing problem using machine learning techniques

handson-ml icon handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

hcvrp icon hcvrp

Heterogeneous capacitated vehicle routing problem

imbalanced-learn icon imbalanced-learn

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

industry-machine-learning icon industry-machine-learning

A curated list of applied machine learning and data science notebooks and libraries across different industries.

inventory-routing-problem-irp- icon inventory-routing-problem-irp-

It can be described as the combination of vehiclerouting and inventory management problems, in which a supplier has to deliver products to a number of geographically dispersed customers, subject to side constraints. It provides integrated logistics solutions by simultaneously optimizing inventory management, vehicle routing, and delivery scheduling. Some exact algorithms and several powerful metaheuristic and matheuristic approaches have been developed for this class of problems, especially in recent years. The purpose of this article is to provide a comprehensive review of this literature, based on a new classification of the problem. We categorize IRPs with respect to their structural variants and the availability of information on customer demand.

iot-predictive-analytics icon iot-predictive-analytics

Method for Predicting failures in Equipment using Sensor data. Sensors mounted on devices like IoT devices, Automated manufacturing like Robot arms, Process monitoring and Control equipment etc., collect and transmit data on a continuous basis which is Time stamped.

kaggle_mercedes icon kaggle_mercedes

The 11th place solution of Mercedes-Benz Greener Manufacturing competition on Kaggle

marketing-and-retail-analytics icon marketing-and-retail-analytics

In the recent past, e-commerce companies have emerged and flourished in the industry. They offer the convenience to order from a wide variety of options from the comfort of one’s home. But how do they offer these “wide variety of options or products”? To be able to meet the demands of the customers, any e-commerce company would obviously need to st

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