Project: Create a Machine Learning model using Python3 to predict housing prices on the Los Angeles area.

Objective: Use the data available from the Los Angeles Real Estate Dataset from Kaggle to develop a model that can accurately predict housing prices in the area. Gather data for housing prices, demographic information in the local area, transportation, and crime data to form a training and test dataset that can be used to create and evaluate the model.

Task:

1. Gather datasets relevant to this project and load them into your Python3 environment
2. Perform exploratory data analysis on the dataset to understand the properties of the data
3. Explore different Machine Learning algorithms and select the appropriate algorithm for the task
4. Engineer features relevant to the task and prepare to train your model
5. Train, tune and evaluate your model on your test dataset
6. Create a visual representation of the model’s performance
7. Analyze the results of the model and make improvements if possible