Linear Regression, GLMs and GAMs with R

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

Created by: Lazy Programmer Inc.
Artificial intelligence and machine learning engineer

What Will I Learn?

• Derive and solve a linear regression model, and apply it appropriately to data science problems
• Program your own version of a linear regression model in Python
• Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion
• Understand regularization for machine learning and deep learning
• Understand closed-form solutions vs. numerical methods like gradient descent
• Apply linear regression to a wide variety of real-world problems

Requirements

• How to take a derivative using calculus
• Basic Python programming
• For the advanced section of the course, you will need to know probability

Target audience

• People who are interested in data science, machine learning, statistics and artificial intelligence
• People new to data science who would like an easy introduction to the topic
• People who wish to advance their career by getting into one of technology's trending fields, data science
• Self-taught programmers who want to improve their computer science theoretical skills
• Analytics experts who want to learn the theoretical basis behind one of statistics' most-used algorithms