Build an Electricity Demand Prediction Machine Learning Model in Python (End-to-End Tutorial)
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What you’ll learn
- Building XGBoost Machine Learning Model
- Time Series Data Handling
- Feature Engineering for Demand Forecasting
- Machine Learning (XGBoost) for Prediction
- Model Evaluation (RMSE, MAE)
- Understanding Energy Consumption Patterns
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This course includes:
- 1.5 hours on-demand video
- 2 downloadable resources
- Access on mobile and TV
- Closed captions
- Free course
Course content
1 section • 6 lectures • 1h 28m total length
- Project Introduction
- Data Exploration
- Data Cleaning
- Feature Engineering
- Visualization
- XGBoost Model Building
- Basic Knowledge of Python
Description
In this project, you will learn how to build a Machine Learning model with Python. We will build a XGBoost Model that will help us in forecasting of electricity demand in a city.
You will learn how to handle time-series data, create powerful features, train a machine learning model and and evaluate its performance.
Here, we have used a historical data of last 5 years. Based on this data we will predict the future demand using our model.
This is a time series dataset with Per Hour information. In this dataset, we have multiple useful columns like – Temperature, Humidity, Demand etc.
From the datetime column, we created other useful columns like day_of_year, week_of_year, is_weekend, is_holiday etc.
We have used the line chart, box plot for visualization.
Key Learnings:
- Time Series Data Handling
- Feature Engineering for Demand Forecasting
- Machine Learning (XGBoost) for Prediction
- Model Evaluation (RMSE, MAE)
- Understanding Energy Consumption Patterns
We will make use of :
- Python: The core programming language
- Pandas: Data manipulation and analysis
- NumPy: Numerical operations
- Matplotlib & Seaborn: Data visualization
- Scikit-learn: Machine learning utilities
- XGBoost: Gradient Boosting for robust predictions
- Holidays: For national holiday data
Master Energy Forecasting: A Python Project for Electricity Demand Prediction.
Thanks all students !
Who this course is for:
- Anyone wants to learn Machine Learning with Python
Note: The course is free for a limited time and limited to 500 users. Enroll as soon as possible. If it is no longer free, it means you are late, and it has already exceeded its limits.
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