Реализация модели Логистическая Регрессия | Logistic Regression | Линейная модель для классификации

You can support the channel by subscribing to 🎉 https://boosty.to/machine_learrrning 🎉 https://vk.com/machine_learrrning 🎉 You can also donate coins to https://www.donationalerts.com/r/mach... TG channel https://t.me/machine_learrrning VK group https://vk.com/machine_learrrning I teach courses at an online university on programs related to AI and Data Science: https://go.redav.online/13d10800fd8342c0 (Netology) Come to my classes! Courses on the Stepik platform: 1. Python Libraries for Data Science https://stepik.org/a/129105 2. Introduction to Neural Networks (Keras/Tensorflow) https://stepik.org/a/127274 ❓ Questions we'll answer in this video: What's the difference between linear regression and logistic regression? What is likelihood? How to derive the logloss function from likelihood? How to train logistic regression from scratch How to visualize logistic regression predictions 🌟 Logistic Regression. Theory    • Логистическая Регрессия | Logistic Regress...   🌟 Linear Regression    • РЕАЛИЗАЦИЯ ЛИНЕЙНОЙ РЕГРЕССИИ | Линейная р...   🤖 Notebook from the video https://colab.research.google.com/dri... 0:00 Introduction 0:07 Lesson Plan 0:28 What you need to know for the lesson 0:46 Support https://boosty.to/machine_learrrning 0:46 Support https://vk.com/machine_learrrning 1:11 Recalling Linear Regression 1:45 Transition to Linear Classification 3:26 Univariate Logistic Regression 5:25 Training LogisticRegression from sklearn on a single feature 6:23 How to go from linear regression to Logistic Regression 7:46 Predicting Probability Using Predict_Proba in LogisticRegression 8:44 Sigmoid in Logistic Regression 9:02 Logistic Regression in Simple Terms 9:29 Comparing Logistic Regression Models 11:54 Likelihood 12:27 A Simple Example of Calculating Likelihood 13:50 An Example of Calculating Likelihood 15:12 Taking the Logarithm of Likelihood 15:27 Log_Loss from Sklearn 16:48 Deriving Logloss from Likelihood 19:53 Implementing Logistic Regression from Scratch for a Single Feature 20:05 Visualizing the Logloss Loss Function 20:42 Adding a Dummy Single Feature 21:22 Implementing the Logloss Function 22:51 Implementing the Logloss Gradient Function 23:46 The Value of inf, nan for Calculating logloss 24:54 Implementing logistic regression using gradient descent 27:08 Visualizing training logistic regression for one feature 29:36 Multivariate logistic regression 30:01 Training LogisticRegression for two features 31:14 Visualizing logistic regression predictions 32:31 Implementing logistic regression from scratch for two features (this also works for a huge number of features) 34:33 Visualizing training logistic regression 35:42 Lesson summary 36:26 ♡