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Deep Learning Prerequisites: Logistic Regression in Python Course

Deep Learning Prerequisites: Logistic Regression in Python Course

Data science techniques for professionals and students – learn the theory behind logistic regression and code in Python

What you’ll learn

Deep Learning Prerequisites: Logistic Regression in Python Course

  • program logistic regression from scratch in Python
  • describe how logistic regression is useful in data science
  • derive the error and update rule for logistic regression
  • understand how logistic regression works as an analogy for the biological neuron
  • use logistic regression to solve real-world business problems like predicting user actions from e-commerce data and facial expression recognition
  • understand why regularization is used in machine learning

Requirements

  • Derivatives, matrix arithmetic, probability
  • You should know some basic Python coding with the Numpy Stack

Description

This course is a lead-in to deep learning and neural networks – it covers a popular and fundamental technique used in machine learning, data science, and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own logistic regression module in Python.
This course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.

This course provides you with many practical examples so that you can really see how deep learning can be used on anything. Throughout the course, we’ll do a course project, which will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.

Deep Learning Prerequisites: Logistic Regression in Python Course

Another project at the end of the course shows you how you can use deep learning for facial expression recognition. Imagine being able to predict someone’s emotions just based on a picture!

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 won’t use your skills to make data-driven decisions and optimize your business using scientific principles, then this course is for you.This course focuses on “how to build and understand“, not just “how to use”. Anyone can learn to use an API in 15 minutes after reading some documentation. It’s not about “remembering facts”, it’s about “seeing for yourself” via experimentation. It will teach you how to visualize what’s happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.

Suggested Prerequisites:

  • calculus (taking derivatives)
  • matrix arithmetic
  • probability
  • Python coding: if/else, loops, lists, dicts, sets
  • Numpy coding: matrix and vector operations, loading a CSV file

TIPS (for getting through the course):

  • Watch it at 2x.
  • Take handwritten notes. This will drastically increase your ability to retain the information.
  • Write down the equations. If you don’t, I guarantee it will just look like gibberish.
  • Ask lots of questions on the discussion board. The more the better!
  • Realize that most exercises will take you days or weeks to complete.
  • Write code yourself, don’t just sit there and look at my code.

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture “What order should I take your courses in?” (available in the Appendix of any of my courses, including the free Numpy course)

Who this course is for:

Deep Learning Prerequisites: Logistic Regression in Python Course

Content From: https://www.udemy.com/course/data-science-logistic-regression-in-python/

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