Case Studies and Projects in Machine Learning/EDA/DL
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Updated
Jun 18, 2024 - Jupyter Notebook
Case Studies and Projects in Machine Learning/EDA/DL
Keeping Inventory of spare in various service centre to the market demand is always a challenge as most service centres spends significant amount in spare parts inventory costs. In spite of this, availability of spare parts is been one of the problem areas.
In this section, we will estimate airline passengers using time series methods.
Sales forecasting system prototype w/ dashboard using SARIMAX model
This repository is a guide to using various time-series analysis models like ARIMA, SARIMA, and SARIMAX in forecasting the exchange rates of 5 currencies as compared to US Dollars
In this section, we will examine the Statistical Methods in time series analysis.
Improved the accuracy of Bitcoin stock price predictions on ARIMA model by reducing the seasonality factor. Achieved RMSE value of 68.99 after implementation of SARIMAX model to reduce seasonality.
Shell_App is an integrated data analysis and modeling platform, featuring scripts for EDA, ensemble techniques, LightGBM, and SARIMAX modeling. Designed for comprehensive data processing, the repository also includes deployment capabilities via Streamlit for interactive model interactions.
Predicting orders for Glovo
Time Series Analysis of Airline Passenger Data, In this time series forecasting, taking data from kaggle site and applying ARIMA and SARIMAX model to evaluate seasional trends of passenger travelling via airlines.
Using time series modeling to forecast the top 3 zipcodes to invest in Washington state.
This project creates Sales Volume predictions based on historical analysis of product, sales, and purchase data using SARIMAX time series model.
Top-Down Investment Strategy Optimization with Time Series Forecasting
Enhancing Decision Making and Prediction Optimization using the HybridFlow Forecast Model
This analysis seeks to forecast the daily number of car accidents in the county of Denver, Colorado using both traditional time series methods from the statsmodels library, as well as the Prophet forecasting framework as implemented in the prophet library.
Predict the apple stock market price for next 30 days. There are Open, High, Low and Close price has been given for each day starting from 2012 to 2019 for Apple stock.
Development of An Automated Conflict Prediction System by State Space ARIMA Methods
Time Series Forecasting with SARIMAX and XGBoost : Chennai house price prediction
implementation forecasting model on thailand co2 emission datasets
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