CS229a: Applied Machine Learning - Stanford University.
Grading will be based on exams, homework assignments and a final project: Homework 40% Midterm 20% Final project 40%; There will be 5 homework assignments. The lowest HW score will be dropped. Midterm is on October 7.
We have covered a lot of material in CS221. In this handout I do my best to compile the list of skills you are expected to have and topics you are expected to know. The skills and topics fall into three main categories: Using search to solve AI problems, Modeling an AI decision as inference over a network of variables, Solving AI problems by teaching machines to learn from data.
COURSERA ML HOMEWORK - Contact and Communication Piazza is the forum for the class. Please consider removing the solutions. Covers classification and regression algorithms. Two.
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many.
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Equivalent knowledge of CS229 (Machine Learning) We will be formulating cost functions, taking derivatives and performing optimization with gradient descent. Recommended. Knowledge of natural language processing (CS224N or CS224U) We will discuss a lot of different tasks and you will appreciate the power of deep learning techniques even more if you know how much work had been done on these.
CS 189 at UC Berkeley. Introduction to Machine Learning. Lectures: 5-6:30 pm Tu-Th in Pimentel 1 (Berkeley Academic Guide page) Jennifer Listgarten. Make private Piazza post before emailing. Office Hours: (see calendar) Stella Yu. Make private Piazza post before emailing. Office Hours: (see calendar) Week 0 Overview Linear Regression, Features, Hyperparameters and Cross-Validation. Wednesday.