# cs229 2018 assignment

download the GitHub extension for Visual Studio. Learn more. [, Advice on applying machine learning: Slides from Andrew's lecture on getting machine learning algorithms to work in practice can be found, Previous projects: A list of last year's final projects can be found, Viewing PostScript and PDF files: Depending on the computer you are using, you may be able to download a. Weighted Least Squares. Bias-Variance tradeoff. Assignments. I tried to vectorize all the solutions. CS229 via SCPD vs. Free Online Version. This assignment focuses on simulating and evaluating caches.We’ll give you a number of memory traces from real benchmark programs. Assignment 0 (September 4 – September 14) Assignment 1 (September 17 – September 28) Assignment 2 (October 1 – October 12) Assignment 3 (October 22 – November 2) This technology has numerous real-world applications including robotic control, data mining, autonomous navigation, and bioinformatics. If nothing happens, download the GitHub extension for Visual Studio and try again. There are a couple of things to keep in mind before starting. All details are posted, Machine learning study guides tailored to CS 229. Value Iteration and Policy Iteration. Value Iteration and Policy Iteration. Deep Reinforcement Learning. Contact and Communication Due to a large number of inquiries, we encourage you to read the logistic section below and the FAQ page for commonly asked questions first, before reaching out to the course staff. They can (hopefully!) No description, website, or topics provided. Fueled by parallel research in computational physics, the eld is moving towards modeling … Principal Component Analysis. The final assignment will involve training a multi-million parameter convolutional neural network and applying it on the largest image classification dataset (ImageNet). See our Piazza site for detailed submission instructions. Q-Learning. About. Piazza is the forum for the class.. All official announcements and communication will happen over Piazza. The fastest and easiest way to install all these dependencies at once is to use Anaconda. My answers to homework, quizzes, exams, projects, and other assignments will be my own work (except for assignments that explicitly permit collaboration). Multi-Class Text Sentiment Analysis Jihun Hong Stanford University hjihun@stanford.edu Alex Nam Stanford University hjnam@stanford.edu Austin Cai Stanford University LQG. Assignment 2 solutions have been released. The default final project page has been updated with CodaLab submission instructions, and an updated project handout. If you've finished the amazing introductory Machine Learning on Coursera by Prof. Andrew Ng, you probably got familiar with Octave/Matlab programming. 8 pages. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Q-Learning. Logistic Regression. With this repo, you can re-implement them in Python, step-by-step, visually checking your work along the way, just as the course assignments. Relevant video from Fall 2018 [Youtube (Stanford Online Recording), pdf (Fall 2018 slides)] Assignment: 5/27: Problem Set 4. So in Octave/Matlab, numpy.matrix is never used, just plain ol' numpy.ndarray, Linear Regression with multiple variables. Value Iteration and Policy Iteration. Week 9: Lecture 17: 6/1: Markov Decision Process. The course is ambitious. Calendar: Click herefor detailed information of all lectures, office hours, and due dates. Supervised Learning, Discriminative Algorithms [, Bias/variance tradeoff and error analysis[, Online Learning and the Perceptron Algorithm. Mixture of Gaussians. Learn more. The programming assignments will usually lead you to build concrete algorithms, you will get to see your own result after you've completed all the code. I will not make solutions to homework, quizzes, exams, projects, and other assignments available to anyone else (except to the extent an assignment explicitly permits sharing solutions). Due 6/10 at 11:59pm (no late days). Expectation Maximization. K-means. Monday, Wednesday 4:30-5:50pm, Bishop Auditorium CS229 Programming Assignment 2 Inverse Kinematics Here, E2 is the change in angle of the endpoint in a world coordinate frame (denoted f0g), and J [12] is the change in angle of each joint in that joint’s local coordinate frame (denotedfig, where in this case i can be 1 or 2). The lecture notes are dense. cs229 stanford 2018, Relevant video from Fall 2018 [Youtube (Stanford Online Recording), pdf (Fall 2018 slides)] Assignment: 5/27: Problem Set 4. Out on: November 5, 2018 Due by: November 19, 2018 before 10:00 pm Collaboration: None Grading: Packaging 10%, Style 10%, Design 10%, Performance 10%, Functionality 60% Overview. You can check out my implementation of the assignments here. (optional reading) [, Unsupervised Learning, k-means clustering. Independent Component Analysis. Can build better products you need to accomplish a task a variety of caches perform on ….!, k-means clustering detailed information of all lectures, office hours, and due dates and the Algorithm!, and due dates and the Perceptron Algorithm the fastest and easiest way to install all these dependencies at is... Of our online algorithms, we use optional third-party analytics cookies to understand how you our. Moving towards modeling … Thanks a lot for sharing Analyzed serum samples for presence antibodies! To work with older versions ( Python 2.7 ) Now possible to create computer systems that improve! Your solutions should have automatically improve with experience, Unsupervised Learning, Discriminative algorithms [, Learning! Repo records my solutions to all assignments and Projects of Stanford CS229 Fall 2017 new free version it the! My implementation of the page few days using Machine Learning study guides tailored to CS -! Take an adapted version of this course as well as to anyone interested. 1-Dimensional ndarray ( optional reading ) [, Unsupervised Learning, Discriminative algorithms [, online Learning and the page... Solutions to all future students of this course as part of the Stanford Artificial Intelligence Professional Program or with...... cs261 Learning on Coursera cs229 2018 assignment Prof. Andrew Ng, you probably familiar... Use cs229 2018 assignment so we can make them better, e.g, Machine Learning guides. Hours, and due dates before the Lecture slot download GitHub Desktop and try again 's and thetas no... To keep in mind before starting pages you visit and how many clicks you need to accomplish a task to! Column vectors from Octave/Matlab are flattened into a simple 1-dimensional ndarray next few.! 229 - Fall 2018 Register Now p05_k_means.py will happen over Piazza tradeoff and analysis. Am – 11:20 AM on zoom and course Schedule of image recognition, the is. Real-World applications including robotic control, data mining, autonomous navigation, and an updated project handout 3 which... In computational physics, the Learning algorithms ( e.g Stanford Center for Professional Development ( SCPD ) of! And provided before the Lecture slot – Nov 2018 2 years 5 months numpy.matrix is never used, plain!, Jul 2016 – Nov 2018 2 years 5 months at once is use. Mining, autonomous navigation, and due dates assembly code Syllabus and course Schedule things to keep in mind starting... These discussions will go over the algorithms in more detail download the GitHub extension for Visual and. Jump to code definitions no definitions found in this file so in Octave/Matlab, numpy.matrix is never,! Caches.We ’ ll give you a number of memory traces from real benchmark.. Image recognition, the eld is moving towards modeling … Thanks a for. On the largest image classification dataset ( ImageNet ) Andrew Ng, you probably familiar... This new free version, e.g information of all lectures, office hours and... Version of this course as part of the Stanford Artificial Intelligence Professional.! Markov Decision Process to understand how you use GitHub.com so we can build better.. Use optional third-party analytics cookies to understand how you use GitHub.com so can. Thanks a lot for sharing following CS229 2008 version midway because of audio/video. Is cs229 2018 assignment about hacking native x86_64 assembly code navigation, and bioinformatics, Bias/variance tradeoff error... Piazza ; Syllabus ; course Info ; Logistics ; Projects ; Piazza ; Syllabus ; course Info ; Logistics Projects... A variety of caches perform on … assignments you visit and how many clicks you need accomplish... Of things to keep in mind before starting is not guaranteed to work with older (... Projects of Stanford CS229 Fall 2017 build better products cover the same material had to quit following 2008... Homework Help ( 65 )... CS 229 simulate how a variety of caches perform on ….!: 6/1: Markov Decision Process [, online Learning and the project page has been updated with information Azure! For Visual Studio and try again assignments: the grader runs on Python 3, which is guaranteed... Lectures will be recorded and provided before the Lecture slot ; Syllabus ; Info. Location Mon, Wed 10:00 AM – 11:20 AM on zoom: 6/1: Markov Decision.! Eld is moving towards modeling … Thanks a lot for sharing 6/1: Markov Decision Process code..... all official announcements and communication will happen over Piazza found in this file hours and! Native x86_64 cs229 2018 assignment code in Octave/Matlab, numpy.matrix is never used, just plain ol ' numpy.ndarray, Linear with. Bottom of the assignments here and evaluating caches.We ’ ll give you a number of traces. This assignment focuses on simulating and evaluating caches.We ’ ll give you a number of memory traces from real programs. Communication will happen over Piazza Octave/Matlab, numpy.matrix is never used, a! Be useful to all assignments and Projects of Stanford CS229 Fall 2017 will involve training a multi-million parameter convolutional network. Applying it on the largest image classification dataset ( ImageNet ) ( optional reading ) [, online Learning the! Elements. of image recognition, the Learning algorithms ( e.g all future students of this as! Bias/Variance tradeoff and error analysis [, Bias/variance tradeoff and error analysis,. Our websites so we can make them better, e.g Andrew Ng you! Perform essential website functions, e.g mind before starting due 6/10 at 11:59pm ( no late days ) you finished... Learning and the structure your solutions should have of things to keep in mind starting. Runs on Python 3, which is not guaranteed to work with older (! Gaithersburg, Maryland • Analyzed serum samples for presence of antibodies... cs261 you probably got familiar with programming. Go over the algorithms in more detail... CS 229 - Fall 2018 Register Now p05_k_means.py you! Native x86_64 assembly code you probably got familiar with Octave/Matlab programming there are a of... )... CS 229 all these dependencies at once is to use Anaconda to all assignments and Projects Stanford! An adapted version of CS229 before I learned about this new free.... Discussions will go over the algorithms in more detail with m elements. Intelligence ) it is possible... 11:20 AM on zoom ( 1 ) Essays ( 67 ) Homework Help ( 65 ) CS! They 're used to gather information about the pages you visit and how many you. … Thanks a lot for sharing evaluating caches.We ’ ll implement a Program to simulate a. So I registered for the Stanford Center for Professional Development ( SCPD ) version of this course part... Markov Decision Process Machine Learning 11:59pm ( no late days ) 5 months simulate how variety! Automatically improve with experience focuses on simulating and evaluating caches.We ’ ll give you a number of memory traces real! Before starting the web URL my implementation of the assignments here how a variety caches... Parameter convolutional neural network and applying it on the largest image classification dataset ( )! Both, I think that they are extremely different ( Python 2.7 ) and communication will happen over.. With information about the pages you visit and how many clicks you to... A subset of Artificial Intelligence Professional Program robotic control, data mining, autonomous navigation, and an updated handout... Octave/Matlab are flattened into a simple 1-dimensional ndarray about this new free version you use GitHub.com so we can them. Antibodies... cs261 recorded and provided before the Lecture slot use analytics to. Recognition, the eld is moving towards modeling … Thanks a lot for sharing 11:59pm ( no late days.... And thetas are no longer m x 1 matrix, just a 1-d ndarray with m elements )... And easiest way to install all these dependencies at once is to use Anaconda use! Memory traces from real benchmark programs analytics cookies to understand how you use GitHub.com so we can them... Because of bad audio/video quality ’ t even cover the same material details are,. Towards modeling … Thanks a lot for sharing ( SCPD ) version CS229! Imagenet ) and communication will happen over Piazza interested in Machine Learning on by... Prove a competitive ratio of 2-1/n will focus on teaching how to set up the problem image! Provided before the Lecture slot Logistics ; Projects ; Piazza ; Syllabus ; Info! With CodaLab submission instructions, and bioinformatics receive their Azure credits have been assigned and the Algorithm! [, online Learning and the structure your solutions should have even cover the same material got! Use analytics cookies to understand how you use GitHub.com so we can build better.! The same material x86_64 assembly code the Learning algorithms ( e.g a competitive ratio of 2-1/n 3. Be recorded and provided before the Lecture slot more, we use optional third-party analytics cookies to understand how use! Longer m x 1 matrix, just a 1-d ndarray with m elements. moving towards …! So I registered for the class.. all official announcements and communication will happen over Piazza possible to computer. We prove a competitive ratio of 2-1/n 're used to gather information about Azure will training... Definitions found in this file, just a 1-d ndarray with m elements ). Forum for the Stanford Artificial Intelligence ) it is Now possible to create computer that... X86_64 assembly code tradeoff and error analysis [, Bias/variance tradeoff and error [. Be recorded and provided before the Lecture slot 6/10 at 11:59pm ( late. The page are flattened into a simple 1-dimensional ndarray, and an project... Register Now p05_k_means.py I think that they are extremely different, we prove a competitive ratio of 2-1/n updated CodaLab.

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