Created by Lazy Programmer Inc.
 Derive and solve a linear regression model, and apply it appropriately to data science problems

Program your own version of a linear regression model in Python
 How to take a derivative using calculus
 Basic Python programming
 For the advanced section of the course, you will need to know probability
 For the advanced section of the course, you will need to know the Gaussian distribution
This course teaches you about one popular technique used in machine learning, data science and statistics: linear regression. We cover the theory from the ground up: derivation of the solution, and applications to realworld problems. We show you how one might code their own linear regression module in Python.
Linear regression is the simplest machine learning model you can learn, yet there is so much depth that you’ll be returning to it for years to come. That’s why it’s a great introductory course if you’re interested in taking your first steps in the fields of:
 deep learning
 machine learning
 data science
 statistics
In the first section, I will show you how to use 1D linear regression to prove that Moore’s Law is true.
What’s that you say? Moore’s Law is not linear?
You are correct! I will show you how linear regression can still be applied.
In the next section, we will extend 1D linear regression to anydimensional linear regression – in other words, how to create a machine learning model that can learn from multiple inputs.
We will apply multidimensional linear regression to predicting a patient’s systolic blood pressure given their age and weight.
Finally, we will discuss some practical machine learning issues that you want to be mindful of when you perform data analysis, such as generalization, overfitting, traintest splits, and so on.
This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for FREE.
If you are a programmer and you want to enhance your coding abilities by learning about data science, then this course is for you. If you have a technical or mathematical background, and you want to know how to apply your skills as a software engineer or “hacker”, this course may be useful.
 People who are interested in data science, machine learning, statistics and artificial intelligence
 People new to data science who would like an easy introduction to the topic
 People who wish to advance their career by getting into one of technology’s trending fields, data science
 Selftaught programmers who want to improve their computer science theoretical skills
 Analytics experts who want to learn the theoretical basis behind one of statistics’ mostused algorithms
Full Courses Download
Content retrieved from: https://www.udemy.com/datasciencelinearregressioninpython/.