Case Study-Boston house price prediction-predicts the price of houses in Boston using a machine learning algorithm called Linear Regression. To train our machine learning model ,we will be using scikit-learn’s boston dataset.
Analyse and visualize data using Linear Regression.
Plot the graph of results of Linear Regression to visually analyze the results.
Linear regression is starting point for a data science this course focus is on making your foundation strong for deep learning and machine learning algorithms.
End of the course you will be able to code your own regression algorithm from scratch.
After completing this course you will be able to:
- Interpret and Explain machine learning models which are treated as a black-box
- Create an accurate Linear Regression model in python and visually analyze it
- Select the best features for a business problem
- Remove outliers and variable transformations for better performance
- Confidently solve and explain regression problems
This course will give you a very solid foundation in machine learning. You will be able to use the concepts of this course in other machine learning models.
Can I download Machine Learning Linear Regression Case Study course?
You can download videos for offline viewing in the Android/iOS app. When course instructors enable the downloading feature for lectures of the course, then it can be downloaded for offline viewing on a desktop.Can I get a certificate after completing the course?
Yes, upon successful completion of the course, learners will get the course e-Certification from the course provider. The Machine Learning Linear Regression Case Study course certification is a proof that you completed and passed the course. You can download it, attach it to your resume, share it through social media.Are there any other coupons available for this course?
You can check out for more Udemy coupons @ www.coursecouponclub.comDisclosure: This post may contain affiliate links and we may get small commission if you make a purchase. Read more about Affiliate disclosure here.
