Deep Learning Prerequisites: Logistic Regression in Python
Deep Learning Prerequisites: Logistic Regression in Python Course
Data science, machine learning, and artificial intelligence in Python for students and professionals
Course Description
This Deep Learning Prerequisites: Logistic Regression in Python 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 Deep Learning Prerequisites: Logistic Regression in Python Course does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.
This Deep Learning Prerequisites: Logistic Regression in Python 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.
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What you’ll learn in Deep Learning Prerequisites 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
Who this Deep Learning course is for:
- Adult learners who want to get into the field of data science and big data
- Students who are thinking of pursuing machine learning or data science
- Students who are tired of boring traditional statistics and prewritten functions in R, and want to learn how things really work by implementing them in Python
- People who know some machine learning but want to be able to relate it to artificial intelligence
- People who are interested in bridging the gap between computational neuroscience and machine learning
