Machine Learning: Regression

Description

Case Study – Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,…). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data — such as outliers — on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets. Learning Outcomes: By the end of this course, you will be able to: -Describe the input and output of a regression model. -Compare and contrast bias and variance when modeling data. -Estimate model parameters using optimization algorithms. -Tune parameters with cross validation. -Analyze the performance of the model. -Describe the notion of sparsity and how LASSO leads to sparse solutions. -Deploy methods to select between models. -Exploit the model to form predictions. -Build a regression model to predict prices using a housing dataset. -Implement these techniques in Python.



More Ways to Learn Machine Learning

Data Mining: Practical Machine Learning Tools and Techniques

High School - College | Book, ebook/Kindle

Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for...

$47

Machine Learning Capstone: An Intelligent Application with Deep Learning

College | Online class

About this Course Have you ever wondered how a product recommender is built? How you can infer the underlying sentiment from reviews? How you can extract information from images to find...

Free

Practical Machine Learning

High School - College | Online class

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction...

Free
Offers paid add-ons

Machine Learning Foundations: A Case Study Approach

College | Online class

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with...

Free

Machine Learning for Data Analysis

College | Online class

Are you interested in predicting future outcomes using your data? This course helps you do just that! Machine learning is the process of developing, testing, and applying predictive algorithms to...

Free

Machine Learning: Classification

High School - College | Online class

Case Studies: Analyzing Sentiment & Loan Default Prediction In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input...

Free
Offers paid add-ons

Machine Learning: Recommender Systems & Dimensionality Reduction

College | Online class

About this Course Case Study: Recommending Products How does Amazon recommend products you might be interested in purchasing? How does Netflix decide which movies or TV shows you might want to...

Free

See all resources for Machine Learning