Python Course — Deep Learning Linear Regression Python
Data science, machine learning, and artificial intelligence with Python for learners and professionals
What You Will Learn
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Derive and solve linear regression models, and apply them correctly to data science problems
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Program your own version of a linear regression model with Python
Requirements
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How to take derivatives using calculus
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Basic Python programming
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For advanced sections of the course, you need to know probability
Description
This course teaches you about one of the popular techniques used in machine learning, data science, and statistics: linear regression. We cover the theory from the ground up: derivation of the solution, and application to real-world problems. We show you how one can code their own linear regression module with Python.
Linear regression is the simplest machine learning model you can learn, yet there is so much depth that you will return 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:
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deep learning
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machine learning
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data science
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statistics
In the first section, we will show you how to use 1-D linear regression to prove that Moore's Law is true.
What do you say? Moore's Law is not linear?
You're right! We will show you how linear regression can still be applied.
In the next section, we will expand 1-D linear regression to linear regression of any dimension – in other words, how to build a machine learning model that can learn from multiple inputs.
We will apply multidimensional linear regression to predict patients' systolic blood pressure based on their age and weight.
Finally, we will discuss some practical machine learning issues you'll want to pay attention to when doing data analysis, such as generalization, overfitting, train-test splits, and more.
This course does not require external materials. Everything you need (Python, and some Python libraries) can be obtained for FREE.
If you are a programmer and want to improve your coding skills by learning about data science, then this course is right for you. If you have a technical or mathematical background, and you want to know how to apply your expertise as a software engineer or "hacker", this course is useful.
