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Logistic Regression with Python from zero to hero

Data science, machine learning, and artificial intelligence in Python for students and professionals

Course Description

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.

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 want to 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.

Goals

  • program logistic regression from scratch in Python

  • describe how logistic regression is useful in data science

  • derive the error and update the 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

Prerequisites

  • Derivatives, matrix arithmetic, probability

  • You should know some basic Python coding with the Numpy Stack

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Curriculum

  • Intro of, course instructor and AI sciences
    03:38
    Preview
  • Motivation for course
    09:43
    Preview
  • Course overview
    05:22
  • Past, present and future of ML
    07:17
    Preview
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Logistic Regression with Python from zero to hero
This Course Includes
  • 8.5 hours
  • 61 Lectures
  • 5 Resources
  • Completion Certificate Sample Certificate
  • Lifetime Access Yes
  • Language English
  • 30-Days Money Back Guarantee

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