Code repository for the book 'Machine Learning in Python for Process and Equipment Condition Monitoring, and Predictive Maintenance'

Predict remaining useful life of a component based on historical sensor observations using automated feature engineering

Evaluating tree-based approaches for timeseries

This Jupyter notebook implements a Bayesian model for (A) fitting the posterior distribution given the data and (B) predicting consumer spending behavior in an e-commerce company. The objective is …

Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.

Perform demand forecasting at the part level rather than the aggregate level to minimize disruptions in your supply chain and increase sales. Manage material shortages and predict overplanning

A software prototype web app for demand forecasting, inventory management and food tracking using machine learning and blockchain.

A software prototype web app for demand forecasting, inventory management and food tracking using machine learning and blockchain.

Used Machine Learning regression models like Logistic regression, Decision Tree to make demand prediction.

Electricity Demand Forecasting: I used numerous ML models and statistical TS forecasting to perform a long-term demand prediction.

A demand forecasting model for an E-Commerce retailer, built using KPIs from Google Analytics & implemented in RStudio. Models: time-series, ARIMA, Regression (multivariate & dynamic). Open-source …

Demand Forecasting using time-series and tree based models for a CPG company that serves US and Canada. Inventory Management using Mixed Integer Linear Programming on the best forecast model.

AlmaBetter Capstone Project -Machine Learning Project type: Regression. This challenge asks you to build a model that predicts the number of seats that Mobiticket can expect to sell for each ride

Six Sigma Green Belt-Enhanced inventory planning process by implementing ML ARIMA model

Data analysis and warehouse planning project using python to provide recommendations for a company's distribution and fulfillment center implementation strategy.

Leverage machine learning techiques to predict Capital Bikesahre demand

Implemented an end-to-end product demand forecasting solution for a company, utilizing historical sales data using Python, SQL and Deployed the forecasting model on the Azure cloud platform using M…

The goal of this project was to explore demand forecasting using R, analyze trends, seasonality, and create ARIMA models to predict future demand. This README provides an overview of the project an…

R package for the Station Demand Forecasting Tool

In today's dynamic marketplace, accurately forecasting product demand is essential for optimizing inventory management, production planning, and ensuring customer satisfaction. This project capital…

A demand forecasting pipeline deployed on Azure and AWS

Interview task submission

利用機器學習方法預測產品的需求量

OneMetric+ project for analytical tool on demand forecast and outlier detection

ARIMA ML Model - Oil and Gas Supply Chain Demand Forecasting with LLM Analysis using AWS Bedrock Foundational Model

Retail Store Demand Forecasting

forcasting customer demand using prophet

The goal of the project is to utilize Recurrent Neural network model (biLSTM) to forecast demand of bike rentals using seasonal and exogenous features

Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAP…