All notes and materials for the CS229: Machine Learning course by Stanford University

Machine learning-Stanford University

Completed the CS231n 2017 spring assignments from Stanford university

All notes and materials for the CS229: Machine Learning course by Stanford University

Stanford LaTeX poster template

Stanford CS193P Fall 2017 Demo

🌲 Stanford CS 228 - Probabilistic Graphical Models

CS131 斯坦福课程课件中英文版

All lecture notes, slides and assignments for CS230 course by Stanford University.

This is an unofficial LaTeX Beamer presentation template for Stanford University.

Unofficial repo for Design and Analysis of Algorithms, Stanford University, Fall 2017.

Solutions to assignments of the CS224W Machine Learning with Graphs course from Stanford University.

Repo for Statistical Learning course offered by Stanford University

Solutions for CS224n course from Stanford University: Natural Language Processing with Deep Learning

PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"

My notes for Stanford's CS229 course

Algorithms - Design and Analysis offered by Stanford University

My solutions for https://www.coursera.org/learn/unsupervised-learning-recommenders-reinforcement-learning

# Machine Learning (Coursera) This is my solution to all the programming assignments and quizzes of Machine-Learning (Coursera) taught by Andrew Ng. After completing this course you will get a broad idea of Machine learning algorithms. Try to solve all the assignments by yourself first, but if you get stuck somewhere then feel free to browse the code. ## Contents * Lectures Slides * Solution to programming assignment * Solution to Quizzes by Andrew Ng, Stanford University, [Coursera](https://www.coursera.org/learn/machine-learning/home/welcome) ### Week 1 - [X] Videos: Introduction - [X] Quiz: Introduction - [X] Videos: Linear Regression with One Variable - [X] Quiz: Linear Regression with One Variable ### Week 2 - [X] Videos: Linear Regression with Multiple Variables - [X] Quiz: Linear Regression with Multiple Variables - [X] Videos: Octave/Matlab Tutorial - [X] Quiz: Octave/Matlab Tutorial - [X] Programming Assignment: Linear Regression ### Week 3 - [X] Videos: Logistic Regression - [X] Quiz: Logistic Regression - [X] Videos: Regularization - [X] Quiz: Regularization - [X] Programming Assignment: Logistic Regression ### Week 4 - [X] Videos: Neural Networks: Representation - [X] Quiz: Neural Networks: Representation - [X] Programming Assignment: Multi-class Classification and Neural Networks ### Week 5 - [X] Videos: Neural Networks: Learning - [X] Quiz: Neural Networks: Learning - [X] Programming Assignment: Neural Network Learning ### Week 6 - [X] Videos: Advice for Applying Machine Learning - [X] Quiz: Advice for Applying Machine Learning - [X] Videos: Programming Assignment: Regularized Linear Regression and Bias/Variance - [X] Machine Learning System Design - [X] Quiz: Machine Learning System Design ### Week 7 - [X] Videos: Support Vector Machines - [X] Quiz: Support Vector Machines - [X] Programming Assignment: Support Vector Machines ### Week 8 - [X] Videos: Unsupervised Learning - [X] Quiz: Unsupervised Learning - [X] Videos: Dimensionality Reduction - [X] Quiz: Principal Component Analysis - [X] Programming Assignment: K-Means Clustering and PCA ### Week 9 - [X] Videos: Anomaly Detection - [X] Quiz: Anomaly Detection - [X] Videos: Recommender Systems - [X] Quiz: Recommender Systems - [X] Programming Assignment: Anomaly Detection and Recommender Systems ### Week 10 - [X] Videos: Large Scale Machine Learning - [X] Quiz: Large Scale Machine Learning ### Week 11 - [X] Videos: Application Example: Photo OCR - [X] Quiz: Application: Photo OCR ## Certificate * [Verified Certificate]() ## References [[1] Machine Learning - Stanford University](https://www.coursera.org/learn/machine-learning)

Stanford course CS193P Fall 2017 Demo for iOS 12 Xcode 10 Swift 4.2

List :clipboard: of Books:books:, Courses :computer: for Data Science :bar_chart:

Problem Set and Programming Assignment Solutions to Stanford University's Algorithms Specialization on Coursera

Stanford University offered CS106A course in the form of '"Code in Place" during the COVID-19 pandemic.

All notes, slides and assignments for CS231n: Convolutional Neural Networks for Visual Recognition class by Stanford

🐲 Stanford CS234 : Reinforcement Learning

Karel Codes

Repo for the Databases courses provided by Stanford University https://lagunita.stanford.edu/courses

The Mini Library System is a text-based Python application that simulates a basic library management tool. Users can add new books, view the list of available or borrowed books, borrow and return books, and save all records locally using file storage. This project was built as part of the final assignment for Code in Place 2025 (Stanford CS106A).

All the solutions from the programming assignments of the Machine Learning Course in Coursera taught by Andrew NG, Professor of Stanford University

A Python API for Stanford's Explore Courses