Project overview
In this project, you’ll assume the role of a data scientist tasked with predicting tomorrow’s weather based on historical data from the Oakland International Airport. You’ll apply skills in data preparation, time series analysis, and machine learning to develop a predictive model.
Throughout the project, you’ll learn how to clean and structure weather data, create relevant features like rolling averages, and build a machine learning model to forecast temperatures. You’ll evaluate your model’s accuracy and learn techniques to fine-tune its performance.
Objective: Use historical weather data to develop a machine learning model that predicts tomorrow’s temperature, building skills in data preparation, model creation, and evaluation.
Key skill required
To complete this project, it's recommended to build these foundational skills in Python
- Working with Python data types, variables, and functions
- Implementing control flow statements like loops and conditionals
- Manipulating data using NumPy arrays and vectorized operations
- Exploring and preparing datasets using the pandas library
Projects steps
Step 1: Project Overview
Step 2: Preparing the Data
Step 3: Filling in Missing Data
Step 4: Verifying Data Types
Step 5: Analyzing Weather Data
Step 6: Training an Initial Model
Step 7: Measuring Accuracy
Step 8: Building a Prediction Function
Step 9: Adding in Rolling Means
Step 10: Adding in Monthly and Daily Averages
Step 11: Next Steps
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