In the third lesson of the Machine Learning from Scratch course, we will learn how to implement the Logistic Regression algorithm. It is quite similar to the Linear Regression implementation, just with an extra twist at the end. You can find the code here: https://github.com/AssemblyAI-Examples/Machine-Learning-From-Scratch Previous lesson: https://www.youtube.com/watch?v=ltXSoduiVwY Next lesson: https://www.youtube.com/watch?v=NxEHSAfFlK8 Welcome to the Machine Learning from Scratch course by AssemblyAI. Thanks to libraries like Scikit-learn we can use most ML algorithms with a couple of lines of code. But knowing how these algorithms work inside is very important. Implementing them hands-on is a great way to achieve this. And mostly, they are easier than you’d think to implement. In this course, we will learn how to implement these 10 algorithms. We will quickly go through how the algorithms work and then implement them in Python using the help of NumPy. ▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬ 🖥️ Website: https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=scratch03 🐦 Twitter: https://twitter.com/AssemblyAI 🦾 Discord: https://discord.gg/Cd8MyVJAXd ▶️ Subscribe: null 🔥 We're hiring! Check our open roles: https://www.assemblyai.com/careers ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #MachineLearning #DeepLearning