This course will teach you the fundamentals of machine learning in Python.
You can jump to any of the course lessons below:
Section 1: Understanding Artifical Neural Networks
- What Is Deep Learning?
- Understanding Neurons in Deep Learning
- Activation Functions
- How Do Neural Networks Really Work?
- Training Neural Networks
- The Role of Gradient Descent in Deep Learning
- Stochastic Gradient Descent in Deep Learning
Section 2: Building Artificial Neural Networks
Section 3: Understanding Convolutional Neural Networks
- Introduction to Convolutional Neural Networks
- What Are Convolutions in Deep Learning?
- Flattening and Full Connection
Section 4: Building Convolutional Neural Networks
Section 5: Understanding Recurrent Neural Networks
- The Intuition of Recurrent Neural Networks
- The Vanishing Gradient Problem
- Long Short-Term Memory Networks (LSTMs)
Section 6: Building Recurrent Neural Networks
Additional details about the instructor and this course are listed below.
I want this course to be a personal experience. Because of that, I have created a Slack community for students to ask questions and interact with each other!
For those unfamiliar, Slack is a team messaging platform primarily used by businesses. Think MSN Messenger, but 10x better. I’ve used Slack in various capacities over the years and have always been pleased with my experience.
Course Repository & Practice Problems
All of the code for this course’s practice problems can be found in this GitHub repository.
The repository is public, which means that you can suggest changes using a pull request later in this course if you’d like.
What To Do If You Get Stuck
If you’re working through this course and are stuck on a difficult problem, here’s what you should do:
- Google for a solution: This is not just me being lazy! Real-world software developers often have to Google for solutions to their problems, so getting practice at this from the start is very beneficial.
- Ask a question in the Slack community: Other students further into this course will be more than willing to help you.
- Email me: You can use this link to email me. While I always love hearing from students, please exhaust the other two options first since I might not reply right away.
My name is Nick McCullum and I have worked in quantitative finance and computer programming for my entire career. I’m currently working as the President of Sure Dividend, where I built our technology stack from scratch, including:
- Python scripts deployed on AWS EC2 and AWS Lambda
- a PostgreSQL relational database on AWS RDS
- a client-facing Wordpress site featuring a members-only login area