CS229

Stanford University

Here are the best resources to pass CS229. Find CS229 study guides, notes, assignments, and much more.

All 8 results

Sort by:

Class notes

Stanford CS229 Notes - Regression Algorithms
-

-

-

12

January 2025

2024/2025
1. Introduction to Linear Regression and Gradient Descent Purpose: Introduces linear regression as a foundational supervised learning algorithm. Content Highlights: Explanation of hypothesis formulation. Detailed notation and definitions (parameters, input vectors, target variables). Step-by-step derivation of cost function
tuningnumbers
$15.49 More Info

Summary

Machine Learning - Linear Regression and Gradient Descent | Lecture 2
-

-

-

1

June 2023

2022/2023
- The lecture discusses linear regression and gradient descent as a learning algorithm. - Linear regression is introduced as one of the simplest learning algorithms for supervised learning regression problems. - The lecture uses the example of predicting house prices to explain the process of building a learning algorithm. - The cost function and the goal of choosing parameters Theta to minimize the cost function are explained. - Batch gradient descent and stochastic gradient descent are int...
reejubhattacherji
$8.49 More Info

Summary

Machine Learning Course, Lecture 1 - Andrew Ng (Autumn 2018)
-

-

-

2

June 2023

2022/2023
- The lecture is an introduction to the Stanford CS229 Machine Learning course. - The course has a long history and has helped many Stanford students become experts in machine learning. - The lecturer, Andrew Ng, introduces himself and the teaching team. - The rise of machine learning has led to an increase in valuable projects and meaningful work. - The lecture covers prerequisites, logistics, and different categories of machine learning tools, including supervised and unsupervised learning...
reejubhattacherji
$9.19 More Info

Class notes

Machine Learning
-

-

-

2

March 2023

2022/2023
This course provides a broad introduction to machine learning and statistical pattern recognition. Learn about both supervised and unsupervised learning as well as learning theory, reinforcement learning and control. Explore recent applications of machine learning and design and develop algorithms for machines.
smiteshkolekar
$12.99 More Info

Class notes

Supervised learning setup
-

-

-

28

February 2022

2020/2021
Supervised learning Linear Regression 1 LMS algorithm 2 The normal equations 2.1 Matrix derivatives 3 Probabilistic interpretation and more
faisalsardar1
$3.99 More Info