斯坦福大学开放课程讲义07-assignment-1

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斯坦福大学机器学习第七讲Lecture7.

斯坦福大学机器学习第七讲Lecture7.

The problem ofoverfittingMachine LearningExample: Linear regression (housing pricesOverfitting:If we have too many features, the learned hypothesis to generalize to new examples (predict prices on new examples.P r i c eSize P r i c eSize P r i c eSizeExample: Logistic regression( = sigmoid function x1x2x1x2x1x2PriceSize size of houseno. of bedroomsno. of floorsage of houseaverage income in neighborhoodkitchen sizeOptions:1.Reduce number of features.―Manually select which features to keep.―Model selection algorithm (later in course.2.Regularization.―Keep all the features, but reduce magnitude/values of parameters .―Works well when we have a lot of features, each of which contributes a bit to predicting .Cost functionMachine LearningIntuitionSuppose we penalize and make , really small. P r i c e Size of house P r i c eSize of houseSmall values for parameters―“Simpler” hypothesis―Less prone to overfitting Housing:―Features:―P arameters:P r i ce Size of houseWhat if is set to an extremely large value (perhaps for too large for our problem, say ? -Algorithm works fine; setting to be very large can’t hurt it-Algortihm fails to eliminate overfitting.-Algorithm results in underfitting. (Fails to fit even training data well.-Gradient descent will fail to converge.What if is set to an extremely large value (perhaps for too large for our problem, say ? P r i c eSize of houseRegularized linearregressionMachine LearningRegularized linear regressionGradient descentRepeatNormal equationSuppose ,Non-invertibility(optional/advanced.(#examples(#featuresIf ,Regularizedlogistic regressionMachine LearningRegularized logistic regression. x2 x1 Cost function: Andrew NgGradient descent Repeat Andrew NgAdvanced optimization function [jVal, gradient] = costFunction(theta jVal = [ code to compute ]; ]; gradient(1 = [ code to compute gradient(2 = [code to compute ]; gradient(3 = [code to compute ]; gradient(n+1 = [ code to compute ]; Andrew Ng。

斯坦福大学公开课教案模版

斯坦福大学公开课教案模版

课程名称:编程方法授课时间:2课时授课对象:计算机科学与技术专业学生教学目标:1. 了解编程方法的基本概念和原则;2. 掌握面向对象、模块化、封装、抽象化与测试等编程思想;3. 熟悉Java语言的特点和应用;4. 培养良好的编程风格。

教学内容:1. 编程方法的基本概念和原则2. 面向对象编程思想3. 模块化、封装、抽象化与测试4. Java语言的特点和应用5. 良好的编程风格教学过程:第一课时:一、导入1. 介绍斯坦福大学编程方法公开课,激发学生学习兴趣;2. 阐述编程方法的重要性,引导学生认识到掌握编程方法对于计算机专业学生的重要性。

二、编程方法的基本概念和原则1. 讲解编程方法的基本概念,如算法、数据结构等;2. 介绍编程方法的原则,如模块化、封装、抽象化与测试等。

三、面向对象编程思想1. 解释面向对象编程的基本概念,如类、对象、继承、多态等;2. 通过实例讲解面向对象编程的优势和应用。

四、模块化、封装、抽象化与测试1. 介绍模块化的概念和作用;2. 讲解封装、抽象化与测试的原则和方法;3. 通过实例分析模块化、封装、抽象化与测试在编程中的应用。

第二课时:一、Java语言的特点和应用1. 介绍Java语言的特点,如跨平台、面向对象、简单易学等;2. 讲解Java语言的基本语法和常用库;3. 通过实例展示Java语言在实际项目中的应用。

二、良好的编程风格1. 强调良好的编程风格对于代码可读性、可维护性的重要性;2. 介绍良好的编程风格,如命名规范、代码格式、注释等;3. 通过实例分析良好编程风格的具体表现。

三、总结与作业1. 总结本节课的重点内容;2. 布置课后作业,要求学生根据所学知识,运用Java语言编写一个简单的面向对象程序。

教学评价:1. 课堂表现:观察学生在课堂上的参与度、提问和回答问题的积极性;2. 作业完成情况:检查学生课后作业的完成情况,评估学生对本节课知识的掌握程度;3. 期末考试:通过期末考试,全面评估学生对编程方法知识的掌握程度。

《斯坦福大学开放课程:编程方法》讲义#1

《斯坦福大学开放课程:编程方法》讲义#1

Mehran Sahami CS 106A Handout #1 September 24, 2007 CS 106A — General Information Based on a handout by Eric Roberts Professor: Mehran SahamiHead TA: Ben NewmanIn addition to lecture, you must also sign up for a weekly 50-minute section. In order to take CS 106A, you must sign up for a section between 5:00 P .M . Thursday, September Special note on discussion sections for SCPD studentsIf you are an SCPD student, you are automatically enrolled in the SCPD discussion section which meets on Fridays from 1:15-2:05 P .M . in Skilling Auditorium (if you would like to come to campus) and is bro adcast live on SITN channel E2 (for remote viewing). Section leaders and course helpersCS106A provides extensive assistance for students. Section Leaders and Course Helpers are available from Sunday through Thursday evenings each week in Tresidder LaIR to/ and click onthe "Helper Schedule" link for the latest schedule of LaIR Helper Hours.If you are an undergraduate, you are required to take CS 106A for 5 units of credit. If you are a graduate student, you may enroll in CS 106A for 3 units if it is necessary for you to reduce your units for administrative reasons. Taking the course for reduced units does not imply any change in the course requirements.Texts and handoutsThere are two required texts for this class, both of which are available from the Stanford Bookstore. The first is a course reader entitled Karel the Robot Learns Java—a 35-page tutorial that introduces the major concepts in programming in the context of an extremelysimple robot world. The second is the textbook The Art and Science of Java by EricRoberts. In addition to these texts, we will also distribute additional material in the form of class handouts. After class, any extra copies of the handouts will be placed in thehandout bins in the entryway to the Gates B-wing. The handouts are also available inPDF® format on the CS 106 web site. If you miss a handout in class, you can print yourown copy from the web.Having an email account is a requirement for this course. E-mail accounts are availableto all students at Stanford through LaIR. Information on obtaining an account is availableat the Tresidder computer cluster, from your Resident Computer Consultant, or via theweb att /.Programming assignmentsAs you can see from the syllabus, there will be seven assignments (Assignment 1 –Assignment 7). The assignments will become slightly more difficult and require moretime as the quarter progresses. Thus, the later assignments will be weighed slightly morethan the earlier ones. Except for Assignment #7 (which is due at the very end of thequarter), each assignment is graded during an interactive, one-on-one session with your section leader, who rates it according to the following scale:++++––––An absolutely fantastic submission of the sort that will only come along a few timesduring the quarter. To ensure that this score is given only rarely, any grade of ++ must be approved by the instructor and TA. Since your section leader would almost certainlywant to show off any assignment worthy of a ++, this review process should not be too cumbersome.A submission that exceeds our standard expectation for the assignment. The programmust reflect additional work beyond the requirements or get the job done in a particularly elegant way.A submission that satisfies all the requirements for the assignment—a job well done.A submission that meets the requirements for the assignment, possibly with a few smallproblems.A submission that has problems serious enough to fall short of the requirements for theassignment.A submission that has extremely serious problems, but nonetheless shows some effortand understanding.A submission that shows little effort and does not represent passing work.From past experience, we expect most grades to be + and . Dividing the grades intocategories means that your section leader can spend more time talking about what youneed to learn from the assignment and not have to worry about justifying each point. The overall goal is to maximize the learning experience in doing the assignments, and wehave found the "bucket" grading system to work much better for programmingassignments than assigning numeric grades from a pedagogical perspective over manyquarters of experience.For each assignment, you must make an appointment with your section leader for an interactive-grading session. Your section leader will explain in section how to schedule these sessions and go over the grading process in more detail.Late policyEach of the assignments is due at the start of class on the dates specified in the syllabus. Most assignments require both electronic and printed submissions. The printed copies may be handed in during class or turned in to the box outside Ben’s office (Gates 160); the corresponding program code must be submitted electronically as described in a separate handout. All assignments are due at 3:15P.M. sharp on the dates indicated on the assignment handout. Anything that comes in after 3:15P.M. will be considered late. Because each of you will probably come upon some time during the quarter where somuch work piles up that you need a little extra time, every student begins the quarter withtwo free "late days." "Late days" are class days, not actual days (i.e. from Monday to Wednesday is one late day). After the late days are exhausted, programs that come in late(up to a maximum of three class days) will be assessed a late penalty of one grade“bucket” per day (e.g., a + turns into a , and so forth). Assignments received later thanthree class days following the due date will not be graded. The interactive-gradingsession with your section leader must be scheduled within two weeks of the due date.Note that late days may not be used on the last assignment (#7) and no assignments willbe accepted after the last day of classes (December 7th).You should think of these free "late days" as extensions you have been granted ahead oftime, and use them when you might have otherwise tried to ask for an extension. As aresult, getting an extension beyond the two free "late days" will generally not be granted.In very special circumstances (primarily extended medical problems or other emergencies), extensions may be granted beyond the late days. All extension requestsmust be directed to the head TA, Ben Newman, no later than 24 hours before the programis due. Only Ben will be able to approve extensions. In particular, do not ask yoursection leader .ExaminationsThe midterm examination will be will be a ninety-minute test administered outside ofclass from 7:00-8:30pm on Tuesday, October 30th. If you have a conflict with thisrequest by electronic mail to me by 5:00pm on Monday, October 22nd to arrange analternate exam time. The final examination is scheduled forThursday, December 13th from 12:15-3:15pm.All examinations are open-book (class course reader and testbook only), and you may use any notes, handouts, or materials from the class, but you cannot use electronic devices of any type (i.e. portable computers, PDAs, etc).GradingFinal grades for the course will be determined using the following weights:45% 30% 15% 10% Programming assignments (weighted toward the later assignments) Final examinationMidterm examinationSection participationComputer facilitiesAs in any programming course, the assignments in CS 106A require extensive hands-on use of a computer. The preferred platform for doing the work is the Eclipse development environment which runs under both Mac OS X and Microsoft Windows (Vista and XP). Instructions on obtaining and using the Eclipse environment—which is an open-source software project and therefore free to download—will be distributed in a separate class handout.。

斯坦福大学自然语言处理第七课“情感分析(Sentiment Analysis)” - 我爱公开课

斯坦福大学自然语言处理第七课“情感分析(Sentiment Analysis)” - 我爱公开课

一、课程介绍斯坦福大学于2012年3月在Coursera启动了在线自然语言处理课程,由NLP领域大牛Dan Jurafsky 和 Chirs Manning教授授课:https:///nlp/以下是本课程的学习笔记,以课程PPT/PDF为主,其他参考资料为辅,融入个人拓展、注解,抛砖引玉,欢迎大家在“我爱公开课”上一起探讨学习。

课件汇总下载地址:斯坦福大学自然语言处理公开课课件汇总二、情感分析(Sentiment Analysis)1)What is Sentiment Analysis?情感分析(Sentiment analysis),又称倾向性分析,意见抽取(Opinion extraction),意见挖掘(Opinion mining),情感挖掘(Sentiment mining),主观分析(Subjectivity analysis),它是对带有情感色彩的主观性文本进行分析、处理、归纳和推理的过程,如从评论文本中分析用户对“数码相机”的“变焦、价格、大小、重量、闪光、易用性”等属性的情感倾向。

更多例子如下:l 从电影评论中识别用户对电影的褒贬评价:l Google Product Search识别用户对产品各种属性的评价,并从评论中选择代表性评论展示给用户:l Bing Shopping识别用户对产品各种属性的评价:l Twitter sentiment versus Gallup Poll of Consumer Confidence:挖掘Twitter(中文:微博)中的用户情感发现,其与传统的调查、投票等方法结果有高度的一致性(以消费者信心和政治选举为例,corelation达80%),详细见论文:Brendan O'Connor, Ramnath Balasubramanyan, Bryan R. Routledge, and Noah A. Smith. 2010. From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. In ICWSM­2010。

《斯坦福大学开放课程:编程方法》讲义#5

《斯坦福大学开放课程:编程方法》讲义#5

Mehran Sahami CS 106A Handout #7 September 26, 2007Assignment #1: Email and Karel the RobotKarel problems due: 3:15pm on Friday, October 5thEmail due: 11:59pm on Sunday, October 7thBased on a handout by Eric RobertsPart II—The REAL Assignment: Karel problems (due 3:15pm on Friday, Oct. 5th) The real problem solving portion of this assignment consists of four Karel programs. There are starter projects for each of these problems on the CS 106 web site in the area for Assignment 1. When you want to work on one of these programs, you need to download that starter folder as described in Handout #6 (Using Karel in Eclipse). Fromth ere, you need to edit the program files so that the assignment actually does what it’s supposed to do, which will involve a cycle of coding, testing, and debugging until everything works. The final step is to submit your assignment using the Submit Project entry under the Stanford menu. Remember that you can submit your programs individually as you finish them and that you can submit more than one version. If you discover an error after you’ve submitted one of these problems, just fix your program and submit a new copy. Also, Please remember that your Karel programs must limit themselvesto the language features described in Karel the Robot Learns Java in the Karel and SuperKarel classes. You may not use other features of Java, even though theEclipse-based version of Karel accepts them.The four Karel problems to solve are described below.Your first task is to solve a simple story-problem in Karel’s world. Suppose that Karelhas settled into its house, which is the square area in the center of the following diagram:543211 2 3 4 5 6 7Karel starts off in the northwest corner of its house as shown in the diagram. The problem you need to get Karel to solve is to collect the newspaper—represented (as all objects in Karel’s world are) by a beeper—from outside the doorway and then to return to its initial position.This exercise is extremely simple and exists just to get you started. You can assume that every part of the world looks just as it does in the diagram. The house is exactly this size, the door is always in the position shown, and the beeper is just outside the door. Thus, all you have to do is write the sequence of commands necessary to have Karel1. Move to the newspaper,2. Pick it up, and3. Return to its starting point.Even though the program is only a few lines, it is still worth getting at least a little practice in decomposition. In your solution, include a private method for each of the steps shown in the outline.A Word of AdviceBefore you go on to the harder problems on this assignment, why don’tyou try submitting your project as soon as you are done with this firstproblem? Every year, a handful of students run into some kind of problemwith the electronic submission option provided in the Stanford version ofEclipse. If you wait until 4:45 P.M. on Friday before you submit any ofyour work, you may discover that there is some aspect of the submissionprocess that you didn’t quite understand only after it’s too late to get anyhelp. So right now, as soon as you’ve got this first program working, goahead and hit the submit button to make sure that you can ship things off.Once you’ve done so, you’ll know that you’ve got the submission processunder control. Remember, we only look at the last submission you makebefore the due date, so it doesn’t hurt to submit new versions of yoursolution as you finish them.Karel has been hired to repair the damage done to the Quad in the 1989 earthquake. In particular, Karel is to repair a set of arches where some of the stones (represented by beepers, of course) are missing from the columns supporting the arches, as follows:876543211 2 3 4 5 6 7 8 9 10 11 12 13Your program should work on the world shown above, but it should be general enough to handle any world that meets certain basic conditions as outlined at the end of this problem. There are several example worlds in the starter folder, and your program should work correctly with all of them.When Karel is done, the missing stones in the columns should be replaced by beepers, so that the final picture resulting from the world shown above would look like this:876543211 2 3 4 5 6 7 8 9 10 11 12 13Karel may count on the following facts about the world, list on the next page:· Karel starts at 1st Avenue and 1st Street, facing east, with an infinite number of beepers. · The columns are exactly four units apart, on 1st, 5th, 9th Avenue, and so forth. · The end of the columns is marked by a wall immediately after the final column. This wall section appears after 13th Avenue in the example, but your program should work for any number of columns. · The top of the column is marked by a wall, but Karel cannot assume that columns are always five units high, or even that all columns are the same height. · Some of the corners in the column may already contain beepers representing stones that are still in place. Your program should not put a second beeper on these corners.Problem 3In this exercise, your job is to get Karel to create a checkerboard pattern of beepers inside an empty rectangular world, as illustrated in the following before-and-after diagram:8 7 6 5 4 3 2 1BeforeAfter1 2 3 4 5 6 7 8 12 3 4 5 6 7 8 This problem has a nice decomposition structure along with some interesting algorithmic issues. As you think about how you will solve the problem, you should make sure that your solution works with checkerboards that are different in size from the standard 8x 8 checkerboard shown in the example. Odd-sized checkerboards are tricky, and you should make sure that your program generates the following pattern in a 5x 3 world:Another special case you need to consider is that of a world which is only one column wide or one row high. The starter folder contains several sample worlds that test these special cases, and you should make sure that your program works for each of them.Problem 4As an exercise in solving algorithmic problems, program Karel to place a single beeper at the center of 1st Street. For example, if Karel starts in the world543211 2 3 4 5it should end with Karel standing on a beeper in the following position:543211 2 3 4 5Note that the final configuration of the world should have only a single beeper at the midpoint of 1st Street. Along the way, Karel is allowed to place additional beepers wherever it wants to, but must pick them all up again before it finishes.In solving this problem, you may count on the following facts about the world:· Karel starts at 1st Avenue and 1st Street, facing east, with an infinite number of beepers in its bag.· The initial state of the world includes no interior walls or beepers.· The world need not be square, but you may assume that it is at least as tall as it is wide. Your program, moreover, can assume the following simplifications:· If the width of the world is odd, Karel must put the beeper in the center square. If the width is even, Karel may drop the beeper on either of the two center squares.· It does not matter which direction Karel is facing at the end of the run.There are many different algorithms you can use to solve this problem. The interesting part of this assignment is to come up with a strategy that works.感谢您试用AnyBizSoft PDF to Word。

斯坦福大学开放课程:七个颠覆你思想的演讲-

斯坦福大学开放课程:七个颠覆你思想的演讲-

And that concept is really to either write information into the brain and the nerve system or read information out of the brain and the nerve system And all this is to heip to address a broad range of neurological diseases and injuries And I will briefly touch upon these wonderfui systems that are able to deliver information into the brain and nerve system But I would primarily focus on this emerging new class of prostheses that aims to read informationout of the brain to heip some of the most paralyzed patients The problem is as simple as the fact that millions of people who aer unable to move or to communicate And the problem is also personal as this photo of Christopher Reeve And as many of you may know that in 1995 he was thrown from his horse and suffered his spinal cord ,broke his neck and from that day forward he was unble to walk ,unble to move his arms ,unble to breathe on his own or unble to even communicate very well due to the respirator he needed And other patients suffer from Lou Gehrig’s diseases and so forth are not even table to speak at all,and nort able to perhaps blink their eyes to communicate.And now we aim to try to help provide new treatment And now we aim to try to help provid new treatment for these severely disabled patients With it also being mind that we can also heip less disabled people,still severely disabled for example with arm amputation,bur perhaps less so.One important here Ithink is important to make is that Chrisper Reed lived all the way up until his death in 2004is a person of considerable means,he had the worid’s best health care.he had the worid’sbest research and he had a foundation that support’s even her own research going full blast to try to remediate us.Stillhis sufferings were so great that diedwithout cured.Now how it mighr be able to offer some quality of life improvement for these patients.Sowhat is shown here is the potential solution to potentially read out neural signals dragged ffrom the brain and use these signals after some interpretations or decrypting if you will to drive prosthetic arms or computer cursors on the screen.we look out,we see where we like to go,we know where our arms are at,we take that information to the rear part of the brain,they were within visual ,which start forming intial plans to move our arms,we elaborate those plans. And those plans and commands descend down this spinal cord to drive the muscles in our arms,to guide the arm where we like it to go.Now if the spinal cord is injured,for example.what we propose to do is to tap into the electrical signals associated with individual neurons.Interpret those neural signals with mathematic algorithms as one on custom-designad chips those of you who are very familiar with this technology,that fuals and all other things running here today.And then deliver those computer signals either to guide the computer cursor on the screen or onto robotic arm to move the arm or perhaps even muscle stimulators to re-animate the paraiyzed arm.the simplest way to express this proposal in a block diagram is that we take sense of this information into the brain.The brain does processing and then ship onto the motor output stages.And as the last link is broken,we might be ableto build effectively a bypassThe way we like to do that is to tap into the region of the brain called pre-motor cortex.Sthe motor cortex is involved in planning,and executing arm movement.So every time you move your arm,that area of the brain with green line starts,become active in particular way.I will tell you more about it in a just second.Take those neural signals out.And if you are looking at a keyboard,we can predict in the real time very rapidly that beat your very single finger typing speed,exactly the letters you like to type and hit,therefore provide a communication mechanism that Christopher Reeve and those similar with him can benefit from.Then how do we do that ?We begin by doing a neural surgical procedure,to implant a silicon based electrode array that you are seeing on the right.And to give a size perspective ,that is about the size of my pinky finger nail,4 mm on the side.100times electrode isonly 1 mm long that penetrates just the most ourer layers of the outer regions of your brain called into the distributable cortex.Each one of those electrodes allows us to measure,we plot voltage verses time.this signal coming feom the tip of that electrode.OK?And this is exactly what the neuron will do all over before going into recepting into a tumor,for example if your have under your brain to know what the different regions of the brains do.Now the trace you notice on the left side has very few and very sharp deflections.And on the right,you notice that there are many of those sharp deflections.And it turns out that simply by cunting the number of those spikes that occurs at a period ofg time.We can interpret what those neurons are saying.Let me play for you,what this neuron recording sounds like.You will hear a quite period and then a louder period .Aquiet period and then a louder a louder period.This is happening while making arm movement from the left into the right.Loud,soft ,loud,soft ,stop.Soit is a very thin and quick move,one on a second,by which I mean that one electrode,one set of neurons is the a very important piece of the puzzle,but not all that you need.What we are hearing were period of quietness and period of a lot of action potentials.And it turns out that when it was quiet,the arm was moving to the left.When it was louder, the arm was moving to the right.Now because it is so important to understand how the neurons present the information,let me go into a bit more detail.OK?This slide and the next will effectively teach you how to design neural prostheses I don’t recommend you do this in your garage at home tonight.But you could.So we were with races monkeys for 2 reasons.But you could.So we were with races monkeys for 2 reasons.One, we can train them to parform these elaborate eye and arm movement tasks as you are seeing here I will describe.Second, we take it very seriously that we need to translate the work we do to humans.Their brains are close so close to humans.What we learned in the monkeys directly moves to humans,that is our on-going goal.We train monkeys to look and touch.A point right on the screen mush like you might do when playing a video game.A point comes on, for example here shown down,but it might come on anywhere on the screen,And at that moment the monkey srarts planning to reach thar location,because he knows that at some period of time,a second or two ,the central light would turn off,telling him reach that location,then he can get a drop of juice as reward .Now what we do is to record the number of those action potrntials in some period of time,and plot them on the graph below.So, when he was reaching down to the right.for example,the yellow circle up here bended green.the green is kept at 40 spikes per second,we might have heard “ke…”.40 of those spikes per second.Now when it reaches up to the right more toward the heart of that red zone ,we may hear “keri….”100 spikes per second.We perceived over a period of 5 or 10 minutes to have made all those arm movements.Plan and reach ,plan and reach,plan and reach.And we can map out this coior map.Now we can play a little game.To the monkleys we show them the spots ,to us ,we will put up keys on the key board.Key are just targets at special locations.SOif we heard”ke…”.a 100 spikes per second ,if me ask you :”where he is planning to resch?”You wouid say :”E key”.it is the only region that responses to 100 spikes per second .Now if we have heard keri…40 spikes per second.Now,where does he want to reach?We do not know.G,A,B,C,D,there is an ambiguity.There is an ambiguity because the neuron does not respond in the same way.Amd this makes the point that one neuron shown here is very important.It is like one piece of jack puzzle.But it does n’t tell us the whole story.To get to the whole story,we have to record from hundred of neurons.And we can do that with the electrode array thar I previously showed you.From each alactrode records from one or more neurons.That will produce a response pattern like this,so each square corresponses how any oneneuron response.And if we actually saw this,we wouid be in trouble.It is like a hundred of the same jack puzzle”p”.So it doesn’t really help us..Fortunately,the brain is not organized that way.Instead,what we see is a different pattern from every neuron.So we can play a final little game here by thinking about having somebody sitting in a room planning to reach up into the left.what we will have come to us,is a corresponding response from every neuron,for example in the upper left,you would see a green little hole.Acouple over it is red and so forth.What you gat at the end of the day is a colored piace,corresponding to the responses modal of neurons that uniquely talls us that the patients want us to reach over to the left and up.We can do that by intercepting our observation with the date base and knowledge we required,the whole color map.So as to predict that location.Now,what I love to is to take you over to the lab and show you how this works.Instead ,we will again play a little game.We will foego the brief neuron surgery.Ok?We out it all to our lab,and tjis will be what we are doing.So,our monkeys look and touch.we may turn onto a targat ,we record from a whole array.W e receive the electric signals from each tip,we tell which neuron is listening to,we get that color pieceAnd then we predict which target he wants to go to.And he gets a drop of juice.And a cursor around the target tells us he did it correctly,THE game we play unfortunmately does not involve with any juice.If you sit in your chairs and look at this keyboard,and elax your muscles and imagine moving your right arm up and hitting the “s”key.And I could go recall from roght above here on the left side of your brain,right in the premium of the cortex to predict exactly that key.And I can do that very fast.Once I do that ,I can move the “s”up there.And we can keep doing”T”,”A”,””N”,and I think you see where it is going .what I dare to say though ,Berkley?NO,and ,ok.All of a sudden ,what we ‘ve just done here is that we’ve just mimicked what it is like to think of a movement,have it read out and predicting locations and typing out a message,which can provide a communication channelto a physician or loved ones if you are severely communication disabled.And right before the last slide,what does it look like in the lab,what we have been able to achieve is a system that performs about 15 words per minute.The typing coming from here is going at that rate,being Stanford alumni,of course the first thing you could type here would be Shakespeare.So,we’ve matched to that ,and two observations.First of all ,this is much faster.By a fact faster than anything being done previously.this is very encouraging to see that we can design this system much more quickly that may offer real benefit to patients to offset that surgical risk.The second thing is that this is still not lightening fast.You can certainly beat this with a ticking of finger typing.But maybe it is on power with one finger.We believe that there is a lot more progress that can be made.And we can go up to much much faster rate.So in conclusion,we certainly hope that the title of Christopher Reeve’s second book is actually possible.That there is nothing impossible that we can provide some new hope for these patients,More encouraged not only by the performance results that I’ve showed you,but also as showed on the right here as recently as last month with one of our collaborators in Utah in producing not only the electrode you see at the bottom,but also on the top of the custom-designed chips with very low power as well electrical coils allows us implant all of that.Again,the size is of your pinky finger nail,all within the skin so you can just turn out your information to drive,for example a replaced arm or a computer screen.think you。

斯坦福大学公开课《机器人学》课程简介

斯坦福大学公开课《机器人学》课程简介

斯坦福大学公开课《机器人学》课程简介01机器人历史及机器人的应用[主题:课程概要,机器人历史的视频,机器人应用,相关的斯坦福机器人课程,讲座和阅读计划,机械臂运动学,机械臂动力学,机械臂控制,机械力臂控,前沿论题02空间描述,广义坐标主题:空间描述,广义坐标,操作坐标,旋转矩阵,旋转矩阵实例,转化,齐次变换实例,操作方法,通用操作方法03东芝公司开发的柔性致动器机器人学导论第三课开始的视频介绍了东芝公司开发的柔性致动器,体积小,由气压驱动,可以简单模仿手脚的运动。

接着本课介绍了齐次变换的几个功能:描述坐标系;旋转或平移矢量以及得到某一矢量在另外坐标系的描述,即映射。

此外,还有作为运算式的齐次变换转换。

齐次变换即为已知某个矩阵和多个坐标系时,将它们相乘即可。

如果已知所有坐标系间的关系,基座也是固定的,于是就可以计算出末端执行器的位置,进而得到基座的位置。

如果一组变换只有一个是缺失的,就可以通过它与其它坐标系的关系确定出来。

表达式包括空间的描述和旋转的表述,具体来说就是如何在空间中定位末端执行器以及怎样把它移动到某个位置。

最后本课讨论了如何运用三个角的表述来表示坐标系的变换、奇异性、固定角以及欧拉参数等问题,并围绕着这些基本问题讨论了欧拉角,旋转等具体实例。

04机器人“蜂鸟”机器人学第四课主要介绍了如何通过各个连杆和末端执行器来控制一个机械手,也就是建立正运动学。

本课首先播放机器人“蜂鸟”的视频来演示机械臂的快速工作过程,然后实际地利用学过的坐标系变换和描述来分析一个机械手。

末端执行器通过连杆连接到基座上,连杆之间接有关节轴。

用DH参数描述连杆,可以精确地定义坐标系。

每一个连杆可以附着一个坐标系,通过设置不同的参数,进行坐标变换,最终得到一个可以用在所有坐标系中的总的变换,接着就可以建立正运动学了。

05灵长类仿生机器人机器人学导论第五课主要介绍了悬臂运动的理论依据以及一个实际的例子。

首先通过一个短片讲解了灵长类仿生机器人和悬臂运动的由来。

斯坦福大学开放课程讲义03-course-placement

斯坦福大学开放课程讲义03-course-placement

Steve Cooper Handout #3CS 106A January 3, 2011Course Placement InformationComputers are everywhere in today’s world. The more you know about computers, the better prepared you will be to make use of them in whatever field you choose to pursue. Learning to program computers unlocks the full power of computer technology in a way that is both liberating and exciting. At the same time, programming is an intellectually challenging activity that comes easily to very few people. Taking a programming course requires a great deal of work and commitment on your part, but you will not be able to master programming without putting in that level of work somewhere along the way. The payoffs, however, are quite real. If you make the effort and keep up with the demands of the material, you will be able to make computers do amazing things. As you begin your journey in computing at Stanford, it would serve you well to decide what are the best options for you along this route.What introductory programming course should I take?A very large percentage of Stanford students take a programming course from the Computer Science Department at some point during their undergraduate career. Because we need to accommodate students with a wide range of backgrounds and interests, the CS department offers several different introductory classes:•CS 101 – Introduction to Computing Principles. This is a new course to introduce the essential idea of Computer Science for a zero-prior-experience audience. CS101 fills a similar niche to CS105, in terms of appealing to students who take the course primarily to meet the Stanford General Education Requirement in category DB-EngrAppSci. The design of CS101 put an emphasis on creating engaging, interesting assignments that get at the key ideas of computer science by experimenting with computer code, but without bogging down too much in programming detail. This is a difficult balance to strike, but it's a priority for CS101. The CS101 assignments and exercises are geared to be done live in class. CS101 is being offered in the Winter quarter this year.•CS 105—Introduction to Computing. This course is designed as a general-education introduction to what this rapidly expanding field of computer science is all about. It attracts an audience of approximately 500 students a year, most of whom take the course primarily to meet the Stanford General Education Requirement in category DB-EngrAppSci. If your only interest is in meeting that requirement, CS 105 is likely to be the most appropriate course. Like any programming course, CS 105 requires a reasonable amount of work, but not as much as CS 106A. CS 105 is offered in Autumn, Winter, and Spring quarter this year.•CS 106A—Programming Methodology. This course is the largest of the introductory programming courses and is one of the largest courses at Stanford (taken by approximately 900 students a year). CS106A teaches the widely-used Java programming language along with good software engineering principles. The course is explicitly designed to appeal to humanists and social scientists as well as hard-coretechies. In fact, most CS 106A graduates end up majoring outside of the School of Engineering. The course requires no previous background in programming, but does require considerable dedication and hard work. CS106A is offered in Autumn, Winter, and Spring quarter this year.•CS 106B—Programming Abstractions.This course is the natural successor to CS 106A and covers such advanced programming topics as recursion, algorithmic analysis, and data abstraction using the C++ programming language, which is similar to both C and Java. If you've taken the Computer Science AP exam and done well (scored 4 or 5) or earned a good grade in a college course, CS106B may be an appropriate course for you to start with, but often CS106X is a better choice. CS106B assumes that you already have familiarity with good programming style and software engineering issues (at the level of CS106A), and that you can use this understanding asa foundation on which to tackle new topics in programming and data abstraction.CS106B is offered in the Autumn, Winter, and Spring this year.•CS 106X—Programming Abstractions (Accelerated). CS106X currently operates as an "honors" version of our CS106B course. It is taught using the C++ programming language and covers the same topics as CS106B but with more in-depth coverage in some areas. In order to get through that much material in a quarter, CS 106X moves at a very fast pace. Students are expected to have solid background comparable to our CS106A course, and should have sufficient maturity and dedication to tackle an intense challenge. If you’ve had previous programming experience, this class is an excellent way to learn C++ and brush up on your skills. If you haven’t done much programming before or don't feel comfortable with your programming skills, you should take the CS 106A/B sequence instead. Don’t let anyone tell you that ―real engineers take CS 106X.‖ These days, most c omputer scientists and engineers start with CS 106A, where they do just fine. The last thing you want to do is get in over your head. If you think you are ready for CS106X, you might want to see how you feel about the course expectations and pace after attending the first few classes. CS 106X is offered in Autumn and Winter quarter this year.Note: Students who have previously taken CS106A and wish to enroll in CS106X in place of CS106B are free to do so. You just need be prepared for a fast paced course.I already know how to program—shouldn’t I skip the intro courses altogether? Many students entering Stanford today have had considerable programming experience in high school or from their own independent work with computers. If you are in that position, the idea of starting with a beginning programming course—even an intensive one like CS 106X—seems like a waste of time. Your perception may in fact be correct. In my experience, there are at somewhere between 10 and 15 students in each entering class who should start at a more advanced point in the sequence. For most of you, however, the right place to start is with the CS 106 series. Most high-school computing courses are quite weak and provide very little background in modern software engineering techniques. By taking CS 106, you will learn how the CS department atStanford approaches programming and get a solid foundation for more advanced work. If you’re unsure where you should start the prog ramming sequence, please talk with me. Other coursesAs computers become more powerful, it is possible to use them for increasingly sophisticated tasks without engaging in programming, at least in a traditional sense. The CS 106 courses teach you about programming, and not about a particular programming language.If your goal is knowing more about how to use computers, you should investigate the following courses:•CS 1C—Introduction to Computing at Stanford. This one-unit course is offered in the Autumn quarter only and makes sure you have a level of ―computer literacy‖ that will allow you to function effectively at Stanford. It does not teach programming at all. •CS 2C—Multimedia Production.This course covers topics related to editing and publishing mulitmedia (sound, image, and video), including using applications like Photoshop and iMovie. Like CS 1C, this course does ot teach programming and requires no programming experience.If, on the other hand, you already have programming experience and want to learn about specific languages and tools, you should check out the following courses:•CS 142—Web Applications. This course covers the concepts and techniques used in constructing interactive web applications. It requires substantial prior programming experience (prerequisites: CS107 and CS108). It will be offered during Autumn quarter this year.•CS 193C—Client-Side Internet Technologies.This course covers such client-side web-oriented topics as JavaScript, XHTML, CSS, XML, and Flash. The course requires previous programming experience at the level of CS106A. It will likely only be offered during Summer quarter this year.•CS 193P—iPhone and iPad Application Programming.As the name implies, this course charts the development path for a iPhone and iPad applications It requires prior programming experience (prerequisites: CS106B/X as well as familiarity with the C programming language). It will be offered during Autumn quarter this year.。

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Steve Cooper Handout #7CS 106A January 5, 2011 Assignment #1: Email and Karel the RobotKarel problems due: 3:15pm on Friday, January 14th This assignment consists of four Karel programs. There is a starter project including all of these problems on the CS 106 web site in the area for Assignment 1. When you want to work on these programs, you need to download that starter folder as described in Handout #6 (Using Karel in Eclipse). From there, you need to edit the program files so that the assignment actually does what it’s supposed to do, which will involve a cycle of coding, testing, and debugging until everything works. The final step is to submit your assignment using the Submit Project entry under the Stanford Menu. Remember that you can submit your programs as you finish them and that you can submit more than one version of your project. If you discover an error after you’ve submitted one of these problems, just fix your program and submit a new copy. Also, Please remember that your Karel programs must limit themselves to the language features described in Karel the Robot Learns Java in the Karel and SuperKarel classes. You may not use other features of Java, even though the Eclipse-based version of Karel accepts them.The four Karel problems to solve are described below.Your first task is to solve a simple story-problem in Karel’s world. Suppose that Karel has settled into its house, which is the square area in the center of the following diagram:123456712345Karel starts off in the northwest corner of its house as shown in the diagram. The problem you need to get Karel to solve is to collect the newspaper —represented (as all objects in Karel’s world are) by a beeper—from outside the doorway and then to return to its initial position.This exercise is extremely simple and exists just to get you started. You can assume that every part of the world looks just as it does in the diagram. The house is exactly this size, the door is always in the position shown, and the beeper is just outside the door. Thus, all you have to do is write the sequence of commands necessary to have Karel 1. Move to the newspaper, 2. Pick it up, and3. Return to its starting point.Even though the program is only a few lines, it is still worth getting at least a little practice in decomposition. In your solution, include a private method for each of the steps shown in the outline.Karel has been hired to repair the damage done to the Quad in the 1989 earthquake. In particular, Karel is to repair a set of arches where some of the stones (represented by beepers, of course) are missing from the columns supporting the arches, as follows:12345678Your program should work on the world shown above, but it should be general enough to handle any world that meets certain basic conditions as outlined at the end of this problem. There are several example worlds in the starter folder, and your program should work correctly with all of them.When Karel is done, the missing stones in the columns should be replaced by beepers, so that the final picture resulting from the world shown above would look like this:12345678Karel’s final location and the final direction he is facing at end of the run do not matter.Karel may count on the following facts about the world, listed below:• Karel starts at 1st Avenue and 1st Street, facing east, with an infinite number of beepers in Karel’s beeper bag.• The columns are exactly four units apart, on 1st, 5th, 9th Avenue, and so forth.• The end of the columns is marked by a wall immediately after the final column. This wall section appears after 13th Avenue in the example, but your program should work for any number of columns.• The top of the column is marked by a wall, but Karel cannot assume that columns are always five units high, or even that all columns are the same height.• Some of the corners in the column may already contain beepers representing stones that are still in place. Your program should not put a second beeper on these corners.Problem 3In this exercise, your job is to get Karel to create a checkerboard pattern of beepers inside an empty rectangular world, as illustrated in the following before-and-after diagram. (Karel’s final location and the final direction it is facing at end of the run do not matter.)1234567812345678Before12345678AfterThis problem has a nice decomposition structure along with some interesting algorithmic issues. As you think about how you will solve the problem, you should make sure that your solution works with checkerboards that are different in size from the standard 8x 8 checkerboard shown in the example. Odd-sized checkerboards are tricky, and you should make sure that your program generates the following pattern in a 5x 3 world:12312345Another special case you need to consider is that of a world which is only one column wide or one row high. The starter folder contains several sample worlds that test these special cases, and you should make sure that your program works for each of them.Problem 4As an exercise in solving algorithmic problems, program Karel to place a single beeper at the center of 1st Street. For example, if Karel starts in the world12345it should end with Karel standing on a beeper in the following position:12345Note that the final configuration of the world should have only a single beeper at the midpoint of 1st Street. Along the way, Karel is allowed to place additional beepers wherever it wants to, but must pick them all up again before it finishes.In solving this problem, you may count on the following facts about the world:• Karel starts at 1st Avenue and 1st Street, facing east, with an infinite number of beepers in its bag.• The initial state of the world includes no interior walls or beepers.• The world need not be square, but you may assume that it is at least as tall as it is wide.Your program, moreover, can assume the following simplifications:• If the width of the world is odd, Karel must put the beeper in the center square. If the width is even, Karel may drop the beeper on either of the two center squares. • It does not matter which direction Karel is facing at the end of the run.There are many different algorithms you can use to solve this problem. The interesting part of this assignment is to come up with a strategy that works.。

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