Data science

Bc. Nihar Mukeshbhai Lathiya

Bakalářská práce

Abstract:

In this thesis the development of house size prediction model for a real estate website is presented. This model is a function which requires inputs from customers. These input can be customer’s desired requirements such as location, price, number of bedrooms and bathrooms. Based on these inputs, the model will predict estimated size of the house from which customer can choose the best. For this purpose, I used python and its machine learning libraries like NumPy, Pandas, Matplotlib and Scikit Learn as a tool. These tools are very efficient and helpful to perform task of data cleaning and data modelling on a huge dataset. After data modelling there is introduced the machine learning process, which contains various methods, techniques and machine learning algorithm applications. Finally, I created house size prediction function based on the best suitable algorithm. Machine learning is a huge area of data science studies that could be used in many different ways such as business, health sectors, education etc. This bachelor thesis particularly focused on real estate business and analyse how data science plays revolutionary role in real estate industry.

Keywords

Big data, Data cleaning, Machine learning, Python, Feature engineering, Data science

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 2. 3. 2021

Obhajoba závěrečné práce

• Vedoucí: Ing. Jan Tyrychtr, Ph.D.

Česká zemědělská univerzita v Praze

Provozně ekonomická fakulta

Bakalářský studijní program / obor:
Systems Engineering and Informatics / Informatics