This repo contains three Python Jupyter Notebooks for a tutorial series published on Stackabuse demonstrating a reasonable process for conducting a machine learning / data analytics project from data collection, data cleaning, data exploration, model experimentation and, model evaluation.
- Using Machine Learning to Predict the Weather: Part 1 - Data collection from WeatherUnderground API, Cleaning, and Exploration
- Using Machine Learning to Predict the Weather: Part 2 - Build Linear Regression Model with Sci-Kit Learn
- Using Machine Learning to Predict the Weather: Part 3 - Build Neural Network Model with Tensorflow