Logistic Regression with Python - Beginner To Advanced Level
Data science, machine learning, and artificial intelligence in Python for students and professionals
Updated on Jun, 2025
Language - English
Development ,Data Science,Python
Lectures -61
Resources -5
Duration -8.5 hours
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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
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction to the Course
4 Lectures
-
Intro of, course instructor and AI sciences
03:38
03:38
-
Motivation for course
09:43
09:43
-
Course overview
05:22
05:22
-
Past, present and future of ML
07:17
07:17
Introduction to Machine Learning
14 Lectures
Introduction to Python
18 Lectures
Logistic Regression
25 Lectures
Instructor Details
AI Sciences
Welcome to the epicenter of innovation, where a collective of visionaries, PhDs, and leading practitioners in Artificial Intelligence, Computer Science, Machine Learning, and Statistics unite. Our team hails from the tech titans - Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.
In our commitment to demystify the complex world of tech, we've crafted an extensive series of courses. Tailored primarily for beginners and newcomers, these courses are your gateway into the realms of Machine Learning, Statistics, Artificial Intelligence, and Data Science. We embarked on this journey with a simple goal: to make these advanced concepts accessible, minimizing theory and lengthy texts, allowing eager minds to dive straight into practice.
As our mission evolved, so did our offerings. We now present comprehensive courses that cater to a broader audience, ensuring everyone can navigate and master these fields with ease.
The impact of our courses has been nothing short of remarkable. We've empowered over 100,000 students, transforming them into masters of AI and Data Science. Join us, and be part of this journey of learning and empowerment, where your mastery of the future begins today.
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