Train Logistic Regression from Scratch | Learn Gradient Descent for Sentiment Analysis
Автор: Coursesteach
Загружено: 2026-01-25
Просмотров: 6
Описание:
In this tutorial, you’ll learn how to train a Logistic Regression model from scratch using Gradient Descent.
We walk step by step through how to initialize parameters (theta), apply the sigmoid function, compute the cost function, calculate gradients, and update parameters iteratively until convergence.
Using sentiment analysis on tweets as an example, you’ll understand how logistic regression learns optimal parameters and how cost minimization works through gradient descent.
This video is perfect for machine learning beginners, data science students, and anyone preparing for AI interviews or ML courses.
📌 Topics covered:
Logistic Regression explained
Gradient Descent intuition
Cost function & contour plots
Training theta parameters
Sentiment analysis classification
👉 Next video: Evaluating your Logistic Regression classifier
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