Deep Learning Prerequisites: Logistic Regression in Python
Deep Learning Prerequisites: Logistic Regression in Python
MP4 | Video: 1280x720 | Duration: 5 Hours | 500 MB | Project Files
Author: Lazy Programmer Inc. | Language: English | Skill level: All Levels
MP4 | Video: 1280x720 | Duration: 5 Hours | 500 MB | Project Files
Author: Lazy Programmer Inc. | Language: English | Skill level: All Levels
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 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 !
Requirements:
You should know how to take a derivative
You should know some basic Python coding
Install numpy and matplotlib