HOME / CATALOG / MACHINE LEARNING PROJECTS — MODELLING REAL ESTATE
EARLY ACCESSPYTHON & MACHINE LEARNING PATHLIFETIME ACCESS

Machine Learning Projects — Modelling Real Estate

Self-paced video training — 4 modules, 14 lessons. Work through it at your own pace — every lesson is real recorded training, not slide-reading.

4
MODULES
14
LESSONS
720p
STREAMING
LIFE
ACCESS
▶INSIDE THE COURSE · 14 LESSONS
UNLOCKS INSTANTLY AFTER CHECKOUTSEE THE CURRICULUM ↓

ABOUT THIS COURSE

In this advanced course, students explore deep learning concepts and artificial neural networks (ANN) while focusing on real estate applications. The curriculum covers data analysis techniques, including exploratory analysis and data visualization, before guiding learners through building and evaluating neural network and multiple linear regression models. By the end, students will have practical experience modeling real estate data and insights into the intricacies of machine learning in this domain.

CURRICULUM

4 modules, in order.

14 LESSONS · LIFETIME ACCESS
01Introduction6 LESSONS
▶Course structure

overview of the course structure and what to expect throughout the lessons.

▶What is Deep Learning

introduction to deep learning and its significance in machine learning.

▶What is ANN

explanation of artificial neural networks and their role in deep learning.

▶Important terms in Neural Network

key terminology related to neural networks that is essential for understanding the concepts.

▶How To Make The Most Out Of This Course

tips on how to effectively engage with the course material for better learning.

▶Introduction

a brief overview of the course and its main objectives.

02Analysing Data4 LESSONS
▶Importing library and data

guidance on how to import necessary libraries and datasets for analysis.

▶Exploratory analysis

methods for exploring and understanding the dataset before analysis.

▶Feature Scaling

importance of scaling features for improving model performance.

▶Data Visualization

techniques for visualizing data to gain insights and patterns.

03Neural Network Model3 LESSONS
▶Data Splitting

process of splitting data into training and testing sets for model evaluation.

▶Neural Network Model

construction and implementation of a neural network model.

▶Multiple Linear Regression Model

introduction to multiple linear regression as a foundational modeling technique.

04Thank you1 LESSONS
▶Thank you

expressing gratitude and concluding remarks for the course.

CURATED BY

ChartMastery
CURATED LIBRARY

Selected from experienced educators' training libraries and kept whole — modules, worked examples and walkthroughs exactly as taught.

GOOD TO KNOW

Lessons stream in the browser and remember where you stopped.

Watch on two devices at once — phone, tablet or desktop.

Download buttons are disabled; delivery is encrypted and authenticated per request.

$39 · ONE PAYMENT

Own every lesson, for life.

One payment unlocks all 14 lessons instantly — start with lesson one the moment you check out.