Python Logistic Regression From Scratch Roadmap!
You can Learn:
-Program logistic regression from scratch in Python
-Describe how logistic regression is useful in data science
-Derive the error and update rule
-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
Basics: What is linear classification? What’s the relation to neural networks?
-Solving for the optimal weights
-Project: Facial Expression Recognition
-Effective Learning Strategies for Machine Learning
This 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 does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.
This provides you with many practical examples so that you can really see how deep learning can be used on anything. It 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.
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 is for you. If you have a technical or mathematical background, and you want use your skills to make data-driven decisions and optimize your business using scientific principles, then this is for you.
This is 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 is for you.
-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