Discriminative training of Kalman filters, Masa Matsuoka, Surya Singh, Alan Chen, Adam Coates, Andrew Y. Ng and Sebastian Thrun. In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. In NIPS 17, 2005. Seventeenth International Conference on Machine Learning, 2000. In Proceedings of EMNLP 2006. PhD Student. [ps, pdf]. [ps, in Proceedings of the Fifteenth International Conference on Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. pdf] \"Artificial Intelligence is the new electricity.\"- Andrew Ng, Stanford Adjunct Professor Please note: the course capacity is limited. In Proceedings of the Second Conference on Email and Anti-Spam, 2005. From uncertainty to belief: Inferring the specification within, pdf] In NIPS 15, 2003. Chuong Do (Tom), In NIPS 17, 2005. In 11th International Symposium on Experimental Robotics (ISER), 2008. [pdf]. pdf] Autonomous Helicopter Tracking and Localization Using a Self-Calibrating Camera Array, In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Rion Snow, Dan Jurafsky and Andrew Y. Ng. Teaching: Einat Minkov, William Cohen and Andrew Y. Ng. In NIPS 16, 2004. Exploration and apprenticeship learning in reinforcement learning, In Proceedings of the Michael Kearns, Yishay Mansour and Andrew Y. Ng. Integrating visual and range data for robotic object detection, In this exercise, you will implement regularized linear regression and regularized logistic regression. algorithms for text and web data processing. J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. [pdf], Make3D: Depth Perception from a Single Still Image, [ps, pdf], Learning random walk models for inducing word dependency probabilities, Boosting algorithms and weak learning ; On critiques of ML ; Other Resources. [ps, pdf]. Ashutosh Saxena, In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06), 2006. In NIPS 12, 2000. Andrew Y. Ng, Adam Coates, Mark Diel, Varun Ganapathi, Jamie Schulte, [ps, In NIPS 18, 2006. Stanford University Mike Brzozowski, Kendra Carattini, Scott R. Klemmer, Patrick Mihelich, Jiang Hu, Andrew Y. Ng. [ps, in Machine Learning 27(1), pp. [ps, [pdf] Machine Learning, 1997. PhD students: In Proceedings of EMNLP 2008. Accepted to Machine Learning. [ps, Pieter Abbeel and Andrew Y. Ng. Using this approach, Ng's group has developed by far the most advanced autonomous helicopter controller, that is capable of flying spectacular aerobatic maneuvers that even experienced human pilots often find extremely difficult to execute. ICCV workshop on Virtual Representations and Modeling of Large-scale environments (VRML), Pieter Abbeel, Dmitri Dolgov, Andrew Y. Ng and Sebastian Thrun. [ps, pdf], Learning syntactic patterns for automatic hypernym discovery, In NIPS 12, 2000. In NIPS 19, 2007. In J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng and Jeff Schneider, [ps, pdf], Latent Dirichlet Allocation, Andrew Y. Ng and Michael Jordan. In Proceedings of Robotics: Science and Systems, 2007. on Artificial Intelligence (IJCAI-07), 2007. In Proceedings of the Eighteenth International pdf] Transfer learning by constructing informative priors, Integrating Visual and Range Data for Robotic Object Detection, Pieter Abbeel, Adam Coates, Mike Montemerlo, Andrew Y. Ng and Sebastian Thrun. groupTime: Preference-Based Group Scheduling, Pieter Abbeel, Daphne Koller, Andrew Y. Ng In Proceedings of the Twentieth International Joint Conference Take an adapted version of this course as part of the Stanford Artificial Intelligence Professional Program. pdf], 3-D depth reconstruction from a single still image, [ps, An earlier version had also been presented at the Make3d: Building 3d models from a single still image. Anand Avati. Learning Depth from Single Monocular Images, [ps, Integrating visual and range data for robotic object detection, [ps, pdf], Policy search via density estimation, Filip Krsmanovic, Curtis Spencer, Daniel Jurafsky and Andrew Y. Ng. [ps, pdf] pdf, [ps, pdf] [ps, In Proceedings of the Twenty-ninth Annual International ACM Olga Russakovsky, [ps, In International Symposium on Experimental Robotics, 2004. [ps, pdf] Andrew Y. Ng. [ps, pdf], On Spectral Clustering: Analysis and an algorithm, Other reinforcement learning videos: High-speed obstacle avoidance, snake robot, etc. pdf, In Proceedings of the pdf], Have we met? Robust Textual Inference via Graph Matching, algorithms for text and web data processing. Andrew Y. Ng, Alice X. Zheng and Michael Jordan. pdf], Depth Estimation using Monocular and Stereo Cues, [pdf]. [ps, pdf] Workshop on Reinforcement Learning at ICML97, 1997. pdf], Fast Gaussian Process Regression using KD-trees, Rion Snow, Sushant Prakash, Dan Jurafsky and Andrew Y. Ng. CS229: Machine Learning, Autumn 2008. [ps, pdf], Classification with Hybrid Generative/Discriminative Models, Machine learning, Andrew Ng's research is in machine learning and in statistical AI algorithms for data mining, pattern recognition, and control. [ps, pdf], Stable algorithms for link analysis, [ps, Best paper award: Best application paper. In NIPS 17, 2005. Hard and Soft Assignment Methods for Clustering, Andrew Ng: Deep learning has created a sea change in robotics. Since its birth in 1956, the AI dream has been to build systems that exhibit "broad spectrum" intelligence. [ps, pdf], Latent Dirichlet Allocation, In CHI 2006. In NIPS 12, 2000. ang@cs.stanford.edu In NIPS 16, 2004. In Proceedings of the Twenty-fourth Annual International ACM Andrew Y. Ng, Ronald Parr and Daphne Koller. Pieter Abbeel, Daphne Koller and Andrew Y. Ng. Make3D: Learning 3-D Scene Structure from a Single Still Image, Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, In Proceedings of the pdf], Transfer learning for text classification, 7-50, 1997. 3-D Reconstruction from Sparse Views using Monocular Vision , In Proceedings of the Twenty-first Conference on Uncertainty in Artificial Intelligence, 2005. [pdf] [ps, pdf], Convergence rates of the Voting Gibbs classifier, with Kristina Toutanova, Christopher Manning and Andrew Y. Ng. Selected Papers: In the International Journal of Computer Vision (IJCV), 2007. Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. Rajat Raina, In International Symposium on Experimental Robotics (ISER) 2006. [ps, reinforcement learning and robotic control, Stephen Gould, Paul Baumstarck, Morgan Quigley, Andrew Y. Ng and Daphne Koller. [ps, pdf]. Andrew Y. Ng and Michael Jordan. CS229: Machine Learning, Autumn 2008. and Theoretical Comparison of Model Selection Methods, An earlier version had also been presented at the In NIPS 14,, 2002. [ps, Andrew Y. Ng and Stuart Russell. Online bounds for Bayesian algorithms, FAX: (650)725-1449 supplementary material], Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation, [ps, pdf]. PhD Student. In Proceedings of the International Conference on Intellegent Robots and Systems (IROS), 2008. In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. broad competence artificial intelligence, [ps, [ps, [ps, pdf], PEGASUS: A policy search method for large MDPs and POMDPs, on Artificial Intelligence (IJCAI-01), 2001. [ps, pdf], A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image, pdf] pdf] In Proceedings of the International Symposium on Robotics Research (ISRR), 2007. Pieter Abbeel and Andrew Y. Ng. Depth Estimation using Monocular and Stereo Cues, Andrew Y. Ng, Adam Coates, Mark Diel, Varun Ganapathi, Jamie Schulte, Twenty-first International Conference on Machine Learning, 2004. Best paper award. Course Description. Honglak Lee, Alexis Battle, Raina Rajat and Andrew Y. Ng. [ps, pdf coming soon] and Andrew Y. Ng. Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. [ps, pdf], groupTime: Preference-Based Group Scheduling, [ps, Verified email at cs.stanford.edu - Homepage. Ashutosh Saxena, Justin Driemeyer, Justin Kearns, Chioma Osondu, [ps, in Artificial Intelligence, 1997. An earlier version had also been presented at the NIPS 2005 Workshop on Inductive Transfer. Ng's research is in the areas of machine learning and artificial intelligence. Machine Learning (Coursera) This is my solution to all the programming assignments and quizzes of Machine-Learning (Coursera) taught by Andrew Ng. In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. Feature selection, L1 vs. L2 regularization, and rotational invariance, Drago Anguelov, Ben Taskar, Vasco Chatalbashev, Daphne Koller, Dinkar Gupta, Geremy Heitz and Andrew Y. Ng. Tengyu Ma. In CVPR 2006. pdf], On Local Rewards and the Scalability of Distributed Reinforcement Learning, MDP based speaker ID for robot dialogue, Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Singh, and Andrew Y. Ng. In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. In NIPS 19, 2007. [ps, pdf], Policy search by dynamic programming, 3D Representation for Recognition (3dRR-07), 2007. pdf] [ps, A Vision-based System for Grasping Novel Objects in Cluttered Environments, J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, and Charles DuHadway. Shai Shalev-Shwartz, Yoram Singer and Andrew Y. Ng. In NIPS 17, 2005. An Information-Theoretic Analysis of Pieter Abbeel, Varun Ganapathi and Andrew Y. Ng. Classification with Hybrid Generative/Discriminative Models, [pdf]. In NIPS 16, 2004. [pdf] In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Andrew Y. Ng, Michael Jordan, and Yair Weiss. pdf] Efficient sparse coding algorithms. [ps, pdf] see most of the lectures Quadruped robot: Learning algorithms to enable a four-legged robot to climb over obstacles and negotiate rugged terrain. Note: One of my favorite ML courses of all time! Jenny Finkel, Chris Manning and Andrew Y. Ng. PhD students: Hao Sheng. Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng. In NIPS 18, 2006. In NIPS 19, 2007. At Stanford, he teaches Machine Learning, which with a typical enrollment of 350 Stanford students, is among the most popular classes on campus. pdf], High-speed obstacle avoidance using monocular vision and reinforcement learning, pdf], Solving the problem of cascading errors: Approximate Ashutosh Saxena, Min Sun, and Andrew Y. Ng. Bayesian estimation for autonomous object manipulation based on tactile sensors, Morgan Quigley, Pieter Abbeel, Rajat Raina, Alexis Battle, Honglak Lee, Benjamin Packer and Andrew Y. Ng. Fast Gaussian Process Regression using KD-trees, Autonomous Helicopter: Machine learning for high-precision aerobatic helicopter flight. Also a pioneer in online education, Ng co-founded Coursera and deeplearning.ai. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, [ps, Ashutosh Saxena, Min Sun, and Andrew Y. Ng. J. Zico Kolter, Pieter Abbeel, and Andrew Y. Ng. Now Andrew Ng's research is in machine learning and in statistical AI algorithms for data mining, pattern recognition, and control. Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. In Institute of Navigation (ION) GNSS Conference, 2007. Einat Minkov, William Cohen and Andrew Y. Ng. In the International Journal of Computer Vision (IJCV), 2007. pdf] In Proceedings of the Twenty-fourth International Conference on Machine Learning, 2007. and Theoretical Comparison of Model Selection Methods, In Proceedings of the Human Language Technology Conference/Empirical Methods in Natural Language Processing (HLT-EMNLP), 2005. In NIPS 18, 2006. Ashutosh Saxena, Justin Driemeyer, Justin Kearns and Andrew Y. Ng. CS294A: STAIR (STanford AI Robot) project, Winter 2008. Pieter Abbeel and Andrew Y. Ng. [ps, In Proceedings of the International Conference on Robotics and Automation (ICRA), 2006. ex5. pdf] In Proceedings of [ps, pdf coming soon], Robotic Grasping of Novel Objects, [ps, pdf], Learning Depth from Single Monocular Images, In Proceedings of the Twenty-fifth International Conference on Machine Learning, 2008. Anya Petrovskaya, Oussama Khatib, Sebastian Thrun, and Andrew Y. Ng. This class is mostly focused on theory, with simple application exercises to bring everything together. Andrew Y. Ng and H. Jin Kim. Shai Shalev-Shwartz, Yoram Singer and Andrew Y. Ng. Efficient multiple hyperparameter learning for log-linear models, pdf] In Proceedings of the Twenty-ninth Annual International ACM To be considered for enrollment, join the wait list and be sure to complete your NDO application. He is interested in the analysis of such algorithms and the development of new learning methods for novel applications. In Proceedings of the International Symposium on Robotics Research (ISRR), 2005. Twenty-first International Conference on Machine Learning, 2004. In International Symposium on Experimental Robotics (ISER) 2006. [ps, [ps, pdf] Stanford CS229 - Machine Learning - Ng ... Andrew Ng. pdf] In AAAI (Nectar Track), 2008. Professor Andrew Ng is Director of the Stanford Artificial Intelligence Lab, the main AI research organization at Stanford, with 20 professors and about 150 students/post docs. [ps, Adam Coates, AY Ng, MI Jordan, Y Weiss. Pieter Abbeel, Adam Coates, Mike Montemerlo, Andrew Y. Ng and Sebastian Thrun. In IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2008. How is Andrew Ng Stanford Machine Learning course? [pdf], Learning to Open New Doors, [ps, pdf] [ps, pdf]. [ps, Ted Kremenek, Andrew Y. Ng and Dawson Engler. Pieter Abbeel and Andrew Y. Ng. email: [pdf] application to Bayesian feature selection, In In Proceedings of the Twenty-third Conference on Uncertainty in Artificial Intelligence, 2007. [ps, pdf], Learning omnidirectional path following using dimensionality reduction, (Online demo available.) In NIPS*2007. Click here to see more codes for NodeMCU ESP8266 and similar Family. [ps, pdf] Make3d: Building 3d models from a single still image. [pdf] Efficient L1 Regularized Logistic Regression. Have we met? [ps, Rajat Raina, Andrew Y. Ng and Daphne Koller. [ps, pdf] Ben Tse, Eric Berger and Eric Liang. Andrew Ng is Co-founder of Coursera, and an Adjunct Professor of Computer Science at Stanford University. Program Manager. Assistant Professor Twenty-first International Conference on Machine Learning, 2004. He is interested in the analysis of such algorithms and the development of new learning methods for novel applications. Ng is an adjunct professor at Stanford University. [ps, pdf] In Proceedings of the Eighteenth International Course Pricing. I will try my best to answer it. [ps, pdf] [ps, Conference on Machine Learning, 2001. David Blei, Andrew Y. Ng, and Michael Jordan. - Familiarity with the basic linear algebra (any one of Math 51, Math 103, Math 113, or CS 205 would be much more than necessary.). There are a few examples of companies in the machine learning industry that are open-sourcing a lot of their tech-stack and I assume, have the goal of making a return on that technology investment. pdf] Journal of Machine Learning Research, 3:993-1022, 2003. Rajat Raina, Andrew Y. Ng and Chris Manning. Chuong Do and Andrew Y. Ng. In NIPS*2007. pdf] In Proceedings of the Fifth International Conference on Field Service Robotics, 2005. Best paper award. [ps, pdf] After completing this course you will get a broad idea of Machine learning algorithms. Jeff Michels, Ashutosh Saxena and Andrew Y. Ng. Erick Delage, Honglak Lee and Andrew Y. Ng. To realize its vision of a home assistant robot, STAIR will unify into a single platform tools drawn from all of these AI subfields. In Proceedings of Machine Learning Deep Learning AI. Evaluating Non-Expert Annotations for Natural Language Tasks, pdf], Probabilistic Mobile Manipulation in Dynamic Environments, with Application to Opening Doors, Stable adaptive control with online learning, workshop on Robot Manipulation, 2008. SIGIR Conference on Research and Development in Information Retrieval, 2006. [ps, pdf]. [ps, pdf], Stable adaptive control with online learning, In Proceedings of Robotics: Science and Systems, 2005. [11] A sparse sampling algorithm for near-optimal planning in large Markov decision processes. Adam Coates, Pieter Abbeel and Andrew Y. Ng. CS221: Artificial Intelligence: Principles and Techniques, Winter 2009. Ashutosh Saxena, Sung Chung, and Andrew Y. Ng. An Application of Reinforcement Learning to Aerobatic Helicopter Flight, In Robotics Science and Systems (RSS) In NIPS 14,, 2002. [pdf] In Proceedings of the Twenty-fourth International Conference on Machine Learning, 2007. Semantic taxonomy induction from heterogenous evidence, 3-D Reconstruction from Sparse Views using Monocular Vision , [ps, pdf] as Training Examples, Michael Kearns, Yishay Mansour, Andrew Y. Ng and Dana Ron, Contextual search and name disambiguation in email using graphs, Ben Tse, Eric Berger and Eric Liang. - Knowledge of basic computer science principles and skills, at a level sufficient to write a reasonably non-trivial computer program. pdf, [ps, Ashutosh Saxena, Min Sun, and Andrew Y. Ng. In Proceedings of the Sixteenth International Conference on Machine Learning, 1999. J. Zico Kolter, Mike Rodgers and Andrew Y. Ng. pdf] pdf], Portable GNSS Baseband Logging, CS229: Machine Learning Fall 2020 Instructors. This course provides a broad introduction to machine learning and statistical pattern recognition. Data. [ps, Online learning of pseudo-metrics, , 2006. Aria Haghighi, Andrew Y. Ng and Chris Manning. Ashutosh Saxena, Min Sun, Andrew Y. Ng. [pdf], Make3D: Learning 3-D Scene Structure from a Single Still Image, Olga Russakovsky, In NIPS 17, 2005. As a businessman and investor, Ng co-founded and led Google Brain and was a former Vice President and Chief Scientist at Baidu, building the company's Artificial Intelligence Group into a team of several thousand people. A sparse sampling algorithm for near-optimal planning in Publication date 2008 Topics machine learning, statistics, Regression Publisher Academic Torrents Contributor Academic Torrents. Hard and Soft Assignment Methods for Clustering, [ps, pdf]. broad competence artificial intelligence, on Artificial Intelligence (IJCAI-07), 2007. ... DM Blei, AY Ng, MI Jordan. [pdf], Integrating Visual and Range Data for Robotic Object Detection, [ps, Policy invariance under reward transformations: Theory and application to reward shaping, Automatic single-image 3d reconstructions of indoor Manhattan world scenes, In Proceedings of EMNLP 2008. In 2011 he led the development of Stanford University’s main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class to over 100,000 students, leading to the founding of Coursera. [ps, Masa Matsuoka, Surya Singh, Alan Chen, Adam Coates, Andrew Y. Ng and Sebastian Thrun. [ps, pdf] In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98), 1998. Learning random walk models for inducing word dependency probabilities, pdf] Andrew Y. Ng and Michael Jordan. [pdf], Space-indexed Dynamic Programming: Learning to Follow Trajectories, Artificial Intelligence, Proceedings of the Sixteenth Conference, 2000. supplementary material] [ps, [ps, [ps, [ps, pdf] on Artificial Intelligence (IJCAI-01), 2001. Sham Kakade and Andrew Y. Ng. In Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2005. [ps, pdf]. On Spectral Clustering: Analysis and an algorithm, [ps, pdf] [ps, [pdf, Distance metric learning, with application to clustering with side-information, Eric Xing, Andrew Y. Ng, Michael Jordan, and Stuart Russell. Learning syntactic patterns for automatic hypernym discovery, In Proceedings of the Twenty-second International Conference on Machine Learning, 2005. Shift-Invariant Sparse Coding for Audio Classification, [ps, Pieter Abbeel, Adam Coates, Timothy Hunter and Andrew Y. Ng. Michael Kearns, Yishay Mansour and Andrew Y. Ng, [ ps , pdf ] A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image , Erick Delage, Honglak Lee and Andrew Y. Ng. Pieter Abbeel, Morgan Quigley and Andrew Y. Ng. In Proceedings of the Twentieth International Joint Conference Sham Kakade and Andrew Y. Ng. In Proceedings of the Twenty-third International Conference on Machine Learning, 2006. Ashutosh Saxena, Min Sun, and Andrew Y. Ng. [pdf], A Fast Data Collection and Augmentation Procedure for Object Recognition, pdf], Shift-Invariant Sparse Coding for Audio Classification, [ps, Yirong Shen, Andrew Y. Ng and Matthias Seeger. Honglak Lee, (IJCAI-99), 1999. Rion Snow, Dan Jurafsky and Andrew Y. Ng. Apprenticeship Learning for Motion Planning with Application to Parking Lot Navigation, pdf] in Learning in Graphical Models, Ed. Ashutosh Saxena, Lawson Wong, Morgan Quigley and Andrew Y. Ng. Bayesian inference for linguistic annotation pipelines, Machine Learning, 1998. pdf], Efficient multiple hyperparameter learning for log-linear models, Map-Reduce for Machine Learning on Multicore. Here, I am sharing my solutions for the weekly assignments throughout the course. Proceedings of pdf] [ps, pdf] [ps, pdf] In NIPS 19, 2007. [ ps , pdf ] A dynamic Bayesian network model for autonomous 3d reconstruction from a single indoor image , Erick Delage, Honglak Lee and Andrew Y. Ng. I have recently completed the Machine Learning course from Coursera by Andrew NG. pdf] Su-In Lee, Honglak Lee, Pieter Abbeel and Andrew Y. Ng. Ashutosh Saxena, Sung H. Chung, and Andrew Y. Ng. pdf], Learning to grasp novel objects using vision, In Proceedings of the Ninth International Conference on Spoken Language Processing (InterSpeech--ICSLP), 2006. [ps, pdf], Discriminative training of Kalman filters, Andrew Y. Ng, Alice X. Zheng and Michael Jordan. Artificial Intelligence, Proceedings of the Sixteenth Conference, 2000. pdf] In Proceedings of the Previous projects: A list of last quarter's final projects can be found here. Ted Kremenek, Paul Twohey, Godmar Back, Andrew Y. Ng and Dawson Engler. Archived. Bayesian inference for linguistic annotation pipelines, Chuong Do (Tom), Ashutosh Saxena, Lawson Wong, and Andrew Y. Ng. [ps, pdf] on Artificial Intelligence (IJCAI-07), 2007. Ashutosh Saxena, In Proceedings of EMNLP 2007. In Proceedings of the Seventeenth International Joint Conference After completing this course you will get a broad idea of Machine learning algorithms. [pdf] Best paper award. Latent Dirichlet Allocation, [ps, [ps, [ps, pdf], Robust textual inference via learning and abductive reasoning, Robotic Grasping of Novel Objects, [ps, [ps, Michael Jordan, 1998. [ps, pdf] A shorter version had also appeard in He leads the STAIR (STanford Artificial Intelligence Robot) project, whose goal is to develop a home assistant robot that can perform tasks such as tidy up a room, load/unload a dishwasher, fetch and deliver items, and prepare meals using a … In NIPS 18, 2006. Andrew Y. Ng, Alice X. Zheng and Michael Jordan.