Energy Consumption Prediction

Created Webapp 2 , updated readme , deployed to streamlit online

completed this project

created webapp 1.py

PKL file for Webapp 2

PKL file for Webapp 1

Export to pkl file and Compress Exported Data to Zip

Export of Predictions Report

Export of Dataset Analysis Report

Export of Model Performance Report

Export of Predictions json and Model Config json

Export model performance json and Dataset analysis json file

Export to txt code

Continuation of Last Commit

Export to CSV code

Processing to Export , Feature Important Analysis

Feature drift detection for future data

Generate summary statistics

Generate Future Prediction

energy consumption forecast , temperature vs predicted energy consumption and more graphs

Ensemble Methods and Model Deployment Preparation

Model Interpretation and Explanation , Feature interaction analysis , Business insights and recommendations

the server was down so unable to upload devlog

for 1.5 to 1.7 hrs : worked on Model Diagnostics and Residual Analysis

for remaining hrs : Learning Curves and Model Validation

top 10 features by correlation with target

Feature Importance Analysis

completing my day

Ensemble Methods Implementation , Model Evaluation and Performance Metrics

performance ranking

Adding MLPRegressor and Adaboost Model

website issue so unable to post devlogs

worked on Model Initialization , Model Training and Hyperparameter Optimization

Statistical Tests for Normality and Relationships , Train-Test Split and Preprocessing Pipeline Setup

Data Visualization Dashboard

working on graphs

Statistical Summary , Feature Engineering

Initial notebook structure with basic imports