If you choose to collaborate For shared projects, we also require that you submit the final report from the Also check out Google Colab for free GPU resources. and the NIPS deadline is usually in early June (http://nips.cc/). https://icml.cc/Conferences/2019/Schedule, https://neurips.cc/Conferences/2019/Schedule. Formerly he was Chief Scientist of YP Mobile Labs at YP. 如今有大量的资源可以用来学习计算机视觉技术，那我们如何从众多教程中进行选择呢？哪个值得我们去投入时间呢？ Open access: all rights granted for use and re-use of any kind, by anyone, at no cost, under your choice of either the free MIT License or Creative Commons CC-BY International Public License. In exceptional cases, we can allow a team of 4 people. No, we don't restrict you to only use methods/topics/problems taught in class. Cs229-notes 2 - Lecture Notes Cs229-notes 7a - Lecture Notes Cs229-notes 1 - Lecture Notes Proef/oefen tentamen 6 Februari 2019, vragen Lab Manual - Lab Cs229-notes 3 - Lecture Notes. She is a professor of Computer Science and Mathematics at CDS and the NYU Courant Institute. This will give you access to the course page, and the assignment submission form. Along with the performance on optional problems, we will also consider significant contributions to Piazza and in-class discussions for boosting a borderline grade. Use Newton’s method to maximize some function \(l\) Aakash is a second-year Masters student in the Data Science program at NYU. CS229. your project teammates, please create a private Piazza post. After CS229, if you want to submit your work to a machine learning conference, the ICML deadline will probably be in early February next year (http://icml.cc), Best Poster Award projects. The term project is 40% of the final grade. Mihir is a Master's student in Data Science at the NYU Center for Data Science, interested in computer vision, reinforcement learning, and natural language understanding. He is interested in solving problems in the healthcare domain using machine learning. We will announce on Piazza once this is finalized. Posted on 2019-10-22 | Edited on 2020-09-11 | In Machine Learning, CS229 Symbols count in article: 1.7k | Reading time ≈ 2 mins. 一、网易云课堂： 1、翁恺老师的计算机课程 翁恺个人主页 本身翁恺老师就是浙大计算机学院的优秀教师，在线上授课时间比较长，经验丰富，条理清晰，在保证授课效果的同时，声音也好听简直是大大加分。 2、大学计算机专业课程体系 大学计算机专业 这门课程最大的优点是体系性强。 If you do not do this, you can submit a regrade request and we will fix it, but we will also deduct 1 point. One of CS229's main goals is to prepare you to apply machine learning algorithms to real-world tasks, or to leave you well-qualified to start machine learning or AI research. If you have any concerns working with one of Basic idea of Newton’s method; 1.2. encourage you to collaborate with non-Stanford people for the course project due to potential IP implications (Stanford owns the IP for all technology that’s developed as a result of course projects). David is a data scientist in the office of the CTO at Bloomberg L.P. Note: Only one group member is supposed to submit the assignment, and tag the rest of the group members (do not all submit separately, or on the flip side forget to tag your teammates if you are the group's designated submitter). Sections will be assigned on Tuesday April 9th 2019 If you are assigned to the monday section and monday is a holiday come to the Tuesday section! Homework Submission: Homework should be submitted through Gradescope. The final project is intended to start you in these directions. results and discussion. Keep Updating: 2019-02-18 Merge to Lecture #5 Note 2019-01-23 Add Part 2, Gausian discriminant analysis 2019-01-22 Add Part 1, A Review of Generative Learning Algorithms. (I.e., Does the technical material make sense? Junwon Park . We will post more details about each each on the website and on Piazza. Sreyas is a second year PhD student in the Data Science Program at CDS working with Prof. Carlos Fernandez-Granda and Prof. Eero Simoncelli. Are the proposed algorithms or applications clever and interesting? Be brave rather than timid, and do feel free to propose ambitious things that you're excited about. I am a master student at Beihang University. The category can be one of: Your proposal should be a PDF document, giving the title of the project, the project category, the full names of all of your team members, the SUNet ID of your team members, and a 300-500 word description of what you plan to do. Collaboration Policy: You may discuss problems with your classmates. The CSI Tool is built on the Intel Wi-Fi Wireless Link 5300 802.11n MIMO radios, using a custom modified firmware and open source Linux wireless drivers. Table 1 Set of Tasks 0 5 10 15 20 25 30!100!50 0 found that a linear kernel performs very well for this problem and we chose Sequential Minimal CS229 Project. This course also serves as a foundation on which more specialized courses and further independent study can build. 2019-10-24 阅读(3063) 评论(14) 2019最新的微博语料，可用于预训练语言模型Weibo-BERT词向量等。由于比较时新，对网络流行语的建模可能很有帮助。每个压缩包都有两千多万条，一共5个。大家下载之后也算是有一个亿身家的人了，激动吧。 To submit assignments, you will need to: Homework Feedback: Check Gradescope to get your scores on each individual problem, as well as comments on your answers. Sanyam is a Masters Student in Computer Science at NYU Courant. Yikes, I am sorry. Any programming language is allowed for the project. So, if you'd like to combine your CS229 project with a class X but class X's policies We don't mind you using a dataset that is not public, as long as you have the required permissions to use it. full title of your project. The project proposal is mainly intended to make sure you decide on a project topic and get feedback from TAs early. If that data needs considerable pre-processing  to suit your task, or that you intend to collect the needed Microsoft Office 2019 Activate. This extends to projects that were done in collaboration with research groups as well. Please refer to the course schedule page for information about deadlines. Is this work likely to be useful and/or have impact? You should submit on Gradescope as a group: that This is because a significant amount of work is needed to formulate the problem, List of code, papers, and resources for AI/deep learning/machine learning/neural networks applied to algorithmic trading. We know that most students work very hard on the final class you're sharing the project with. It is okay if two teams end up working on the same project as long as they don’t coordinate to do so, in order to not be biased in the way they tackle the problem. The Adam optimization algorithm is an extension to stochastic gradient descent that has recently seen broader adoption for deep learning applications in computer vision and natural language processing. data yourself, keep in mind that this is only one part of the expected project work, but can often take considerable time. Your milestone should be at most 3 pages, excluding references. Clearly indicate in your milestone and final report, which part of the project is done for CS229 and which part is done for a class other than CS229. This webpage contains instructions to use our 802.11n measurement and experimentation platform. CS229 Note: Linear Regression, Logistic regression, Generalized Linear Models Posted on 2019-10-20 | Edited on 2019-10-23 | In Machine Learning, CS229. NumPy is "the fundamental package for scientific computing with Python." My research interests include differential privacy and artificial intelligence. We still expect a solid methodology and discussion of results, so pace your project accordingly. At the beginning of the semester, you will be added to the Gradescope class roster. This course was designed as part of the core curriculum for the Center for Data Science's Masters degree in Data Science. You can find papers from the recent ICML https://icml.cc/Conferences/2019/Schedule and NeurIPS conference https://neurips.cc/Conferences/2019/Schedule. Notes on a few specific types of projects: This section contains the detailed instructions for the different parts of your project. Rather than emailing questions to the teaching staff, please post your questions on Piazza, where they will be answered by the instructor, TAs, graders, and other students. For group-specific questions regarding projects, please create a private post on Piazza. • Suppose we have a dataset giving the living areas, number of bedrooms and prices of 200 houses from a specific region: • Given data like this, how can we learn to predict the prices of other houses, Please also post a link to these postings in Piazza, so others in the class can answer the questions and benefit from the answers. Please include a link to a Github repository or zip file with the code for your final project. As long as your proposal follows the instructions above and the project seems to have been thought out with a reasonable Two of the main machine learning conferences are ICML and NIPS. Acknowledgements. You do not have to include the data or additional libraries (so if you submit a zip file, it should not exceed 5MB). However, you must write up the homework solutions and the code from scratch, without referring to notes from your joint session. Your milestone should include the full names of all your team members and state the Symbols count in article: 21k | Reading time ≈ 19 mins. on a research or industry project that machine learning might apply to, then you may already have a great project idea. Method: What machine learning techniques have you tried and why? In the proposal, below your project title, include the project category. Many homework assignments will have problems designated as “optional”. don't allow for it, you cannot do it. Motivation: What problem are you tackling, and what's the setting you're considering? However, the project need to focus on model performance and achieve a high leaderboard score to receive high grades. in mind that the intended audience are the instructors and the TAs. One of CS229's main goals is to prepare you to apply machine learning algorithms to real-world tasks, or to leave you well-qualified to start machine learning or AI research. CS 229 projects, Fall 2019 edition. Rita Liao Manish Singh 2 years ... July 28, 2019. We generally don’t Is this an application or a theoretical result? Please tell me by raising a GitHub issue. Each year, some number of students continue working on their projects after completing CS229, submitting their work to a conferences or journals. For registration information, please contact, Some prerequisites may be waived with permission of the instructor, You can also self-assess your preparation by filling out the, (HTF) refers to Hastie, Tibshirani, and Friedman's book, (SSBD) refers to Shalev-Shwartz and Ben-David's book, (JWHT) refers to James, Witten, Hastie, and Tibshirani's book. No, but please explicitly state the work which was done by team members enrolled in CS229 in your milestone and final report. This website is developed on GitHub; feel free to report issues or send feature requests. Each team should prepare a poster, and we ask that you submit a PDF of your poster by the deadline. Stanford CS229 Linear Algebra review. Motivation: What problem are you tackling? Note: We will not be holding a poster session in Fall 2020. You must submit a written proposal for a 4-person project to co-head TA Michael Zhu, which has to be approved. Of course, depending on the topic of Thus, for example, you should not spend two pages explaining what logistic regression is. You cannot turn in an identical project for both classes, but you can share common infrastructure/code base/datasets across the two classes. Thus, for inspiration, DS-GA-1001: Intro to Data Science or its equivalent; DS-GA-1002: Statistical and Mathematical Methods or its equivalent; Solid mathematical background, equivalent to a 1-semester undergraduate course in each of the following: linear algebra, multivariate calculus (primarily differential calculus), probability theory, and statistics. Find me on Twitter! Please include a section that describes what each team member worked on and contributed to the project. Preliminary experiments: Describe the experiments that you've run, the outcomes, and any error analysis that you've done. Please write the milestone (and final report) keeping plan, you should do well on the proposal. Using datasets on Kaggle is allowed. 1.1. If you have not used Gradescope before, please watch this short video: "For students: submitting homework." Recent advances in parameterizing these models using deep neural networks, combined with progress in stochastic optimization methods, have enabled scalable modeling of complex, high-dimensional data including images, text, and speech. The technical quality of the work. ), The novelty of the work. We’ll announce when submissions are open for each part. Problems are motivated by the ones shared at: CMU Machine Learning; Stanford CS229 Machine Learning Projects; Credit. The team size will be taken under consideration when evaluating the scope of the project in breadth and depth, meaning that a three-person team is expected to accomplish with a company, please understand you will need to follow the IP policy here. You should make sure that you follow all the guidelines and requirements for the CS229 project (in addition to the requirements of the other class). Built with lots of keyboard smashing and copy-pasta love by NirantK. The first day of class is on April 8th, 2019 in 200-002. A private repository is recommended (and free with GitHub's Education Pack), but a public repository is also okay. Homeworks will still be accepted for 48 hours after this time but will have a 20% penalty. Do the authors convey novel insight about the problem You should have tried at least one baseline. CS229 Final Project Information. You will then select the appropriate page ranges for each homework problem, as described in the "submitting homework" video. Building the Optimal Book Recommender and measuring the role of Book Covers in predicting user ratings. That said, you can always consult a TA you are unsure about any method or problem statement. If you plan to work on a project in a team of 4, please come talk to one of the TAs beforehand so we can ensure that the project has a large enough scope. In your solution to each problem, you must write down the names of any person with whom you discussed the problem—this will not affect your grade. If you do not want your write-up to be posted online, then please create a private Piazza post We will use Piazza for class discussion. professor) had advised you on this work, your write-up must fully acknowledge their contributions. ), Significance. 4. We don't require you to share the dataset either as long as you can accurately describe it in the Final Report. you might also look at some recent machine learning research papers. Please first have a look through the frequently asked questions. Digression - Perceptron. If you're looking for project ideas, please come to office hours, and we'd be happy to brainstorm and suggest some project ideas. Late days cannot be used for the project. Mingsi is a second year student in the Data Science Program at NYU CDS. The reason we encourage students to form teams of 3 is that, in our experience, this size usually fits best the expectations for the CS229 projects. GRE: Evaluating Computer Vision Models on Generalizablity Robustness and Extensibility. A very good CS229 project will be a publishable or nearly-publishable piece of work. Used in machine learning (&deep learning) to formulate the functions used to train algorithms to reach their objective, known by loss/cost/objective functions. and/or algorithms? more than a one-person team would. (Is this project applying a common technique to a well-studied problem, or is the problem or method relatively unexplored?). data cleaning, cross-validation, and sampling bias). Intended experiments: What experiments are you planning to run? This is to make sure team members are carrying a fair share of the work for projects. Almost the same procedure as the logistic regression. While mathematical methods and theoretical aspects will be covered, the primary goal is to provide students with the tools and principles needed to solve the data science problems found in practice. Since Gradescope cannot distinguish between required and optional problems, final homework scores, separated into required and optional parts, will be posted on NYUClasses. We will not be disclosing the breakdown of the 40% that the final project is worth amongst the different parts, but the poster and final report will combine to be the majority of the grade. about! How do you plan to evaluate your machine learning algorithm? Final project writeups can be at most 5 pages long (including appendices and figures). in contributions and evaluations when assigning project grades. Newton’s Method. If you did this work in collaboration with someone else, or if someone else (such as another awesome-deep-trading. For questions that are not specific to the class, you are also encouraged to post to Stack Overflow for programming questions and Cross Validated for statistics and machine learning questions. At the end of the semester, strong performance on these problems may lift the final course grade by up to half a letter grade (e.g. After the class, we will also post all the final writeups online so that you can read about each other's work. We will all be meeting there from 1:30 to 2:50 pm. We recommend teams of 3 students, while teams sizes of 1 or 2 are also acceptable. Method: What machine learning techniques are you planning to apply or improve upon? (Did the authors choose an interesting or a “real" problem to work on, or only a small “toy" problem? The final project is intended to start you in these directions. CS229 Final Project Information. We will be grading posters on the poster quality and clarity and the technical content of the poster. No, the final report will be submitted via Gradescope. Computer Vision. In particular, we expect the team to submit a completed project (even for team of Late Policy: Homeworks are due at 11:59 PM on the date specified. team from completing the project, you should do well on the milestone. problems. This is just a recommendation; feel free to speak with other TAs as well. For shared projects, we also require that you submit the final report from the class you're sharing the project with. A team can have both on-campus and SCPD students. So, pick something that you can get excited and passionate Please include a section that describes what each team member worked on and contributed to the project. We may reach out and factor
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