Deep Learning Prerequisites: Logistic Regression in Python

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

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

Created by: Lazy Programmer Team
Artificial Intelligence and Machine Learning Engineer

What Will I Learn?

• 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
• Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion

Requirements

• Derivatives, matrix arithmetic, probability
• You should know some basic Python coding with the Numpy Stack

Target audience

• 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