Project Instructions 1. Selection of Project Idea and Data Sets: You are encouraged to come with an original and interesting idea. Make sure that you have identified the relevant data sets. It is preferable to use multiple uncleaned dataset in heterogeneous formats.

2. Data Preparation: You should demonstrate the proper use of data wrangling and preparation techniques, such as categorization, normalization, re-scaling, etc. according to the requirements of your objectives.

3. Model Building and Evaluation: You should choose the most suitable machine learning algorithm(s) and parameter(s) for building the forecast model.

4. Report : A well-structured report (between 3 to 5 pages) should be prepared that will explain the problem, your idea, the data sets, the analysis, results, and discussion.

Problem Statement: A group of Australian farmers is seeking a farm for sale at different cities in Australia. Their main search criterion is focused on weather conditions since the weather has the most significant impact on farm production. Therefore, these formers want to hire a good data scientist who is cable of studying the following dataset: https://www.kaggle.com/jsphyg/weather-dataset-rattle-package . This is to help them decide which cities have the optimal weather conditions in order to buy a farm there.