Dr. Zheng (Thomas) Tang is now a Research Scientist - Amazon One at Amazon.He was an Intelligent Video Analytics Intern at NVIDIA from 2018 to 2019. Alberta Machine Intelligence Institute - Machine Learning Algorithms: Supervised Learning Tip to Tail University of Helsinki: Object-Oriented Programming with Java, part I The Hong Kong University of Science and Technology - Python and Statistics for Financial Analysis -- Perfomed a twitter sentiment analysis on live stream data using Twitter API. Working as a Business Intelligence Consultant, I lead my team through different projects and churning through data for 3 years. Currently pursuing the Data Science specialization at the UW. Optimizing Distributed Systems using Machine Learning phd thesis Ignacio Cano Paul G. Allen School of Computer Science & Engineering, University of Washington, 2019 Hello! -- Exploratory data analysis has been performed on the murder statistics of 2012 in the United States. Learn more. Publications. If nothing happens, download GitHub Desktop and try again. Biography. I earned my PhD studying Machine Learning as a student of Prof. Sham M. Kakade at the University of Washington Seattle. -- Refer the documents via the link for detailed analysis of the techniques and datasets used. Course Materials Fond of data, I was motivated to take up a job in this field. Statistics and Machine Learning. Techniques used: Python, pandas, numpy,scikit-learn, graphlab. I like the interior decoration and the blackboard menu on the wall. I was a teaching assistant for. My research interests include natural language processing, semantic role labeling, multimodal learning for vision and language, and machine learning applications. My first hands on real data. -- Scalable code to run on any twitter dataset. Oracle Certified SQL Expert and Oracle Certified DBA. The goal of the PhD track is to prepare students to tackle large data analysis tasks with the most advanced tools in existence today, while building a strong methodological foundation. My skills include Oracle BI (10G/11G), Microsoft SQL stack, Informatica, SSIS and Hive to name a few. I am broadly interested in safe and interpretable machine learning with applications in natural language processing. • CV • Github • Scholar contact: rkidambi AT cornell DOT edu -- First graph shows top Batsman performance from both the teams, second shows the team results of all the series and the A childhood interest in computers turned into a career path when I completed my undergradute in Computer Engineering from the University of Mumbai with a Distinction Degree. Contribute to tuanavu/coursera-university-of-washington development by creating an account on GitHub. -- Multiple graphs designed in order to explore and visualize the safe and unsafe states with respect to Murder stats. MISC Teaching. ... Machine Learning: License. My Forte. All Solutions licensed under MIT License. As the technology becomes faster and more accessible, machine learning is sparking innovations big and small, from customer service chatbots to … 2015. I have explored explainability and fairness aspects of Machine Learning to make it … MATH 394 (Winter 2021, UW): Probability I. STAT 516 (Autumn 2020, UW): Stochastic Modeling. I received my Ph.D. from Ecole Normale Superieure de Paris under the supervision of Alexandre d’Aspremont within the Sierra Team led by Francis Bach. Graduate Course, University of Washington, Department of Electrical and Computer Engineering, 2019 Teaching Assistant of CSEP 546 Winter 2014: Data Mining/Machine Learning Graduate Course, University of Washington, Paul G. Allen School of Computer Science and Engineering , 2014 Determine when a deep neural network would be a good choice for a particular problem. The UW Department of Statistics now offers a PhD track in the area of Machine Learning and Big Data. -- Created a visualization in D3 to explore the relationship between World Employment vs Internet usage in various countries. 6 Machine Learning Specialization Intelligent restaurant review system ©2015 Emily Fox & Carlos Guestrin All reviews for restaurant The seaweed salad was just OK, vegetable salad was just ordinary. Preprints My wife tried their ramen and it was pretty forgettable. O’Reilly Media, Inc. O’Reilly Media, Inc. Goldstein, Alex, Adam Kapelner, Justin Bleich, and Emil Pitkin. Coursera Assignment and Project. Online Meta-Learning Chelsea Finn, Aravind Rajeswaran, Sham Kakade, Sergey Levine International Conference on Machine Learning (ICML) 2019; arXiv:1902.08438. ... Code open-sourced on Github-- Exploratory data analysis has been performed on the murder statistics of 2012 in the United States.-- Different tabs on the story explore different dimensions. Bio. Contribute to tuanavu/coursera-university-of-washington development by creating an account on GitHub. Graduate student in Atmospheric Sciences researching applications of machine learning to ensemble weather forecasting. As a Data Science for Social Good fellow at the University of Chicago in 2015, I helped develop the Legislative Influence Detector. Machine learning — the ability for computers to detect patterns in data and use it to make predictions — is changing our world in profound ways. My research focuses on pure exploration multi-armed bandits, recommender systems, and nonparametric estimation. Machine Learning courses. -- Designed multiple filters to narrow down search by Country, Region, Income Group, Year and Population. -- Different tabs on the story explore different dimensions. Hands-on Machine Learning with Scikit-Learn and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems. This repo contains lectures and assignments of University of Washington - Coursera. Supervised learning and predictive modeling: decision trees, rule induction, nearest neighbors, Bayesian methods, neural networks, support vector machines, and model ensembles. I am an Assistant Professor of Machine Learning at MILA (Quebec Institute for Learning Algorithms)/HEC Montréal (U. Montreal’s business school). Use Git or checkout with SVN using the web URL. Tutorial on Optimal Transport in Computational Neuroscience, Neurohackademy, 2020.. -- Conducted a survey to analyze the current understanding of the users for home lighting. Kunal Seth - Blending Data and Creativity at Adobe. -- Implemented different Machine Learning Algorithms on different datasets. GitHub - Weenkus/Machine-Learning-University-of-Washington: All code used in the Machine Learning specialization from Coursera at https://www.coursera.org/specializations/machine-learning. Previously, I was a postdoctoral fellow in the NSF-TRIPODS institute ADSI (now IFDS) at the University of Washington.. Here is my resume (as of January 2019) You can also find me on: LinkedIn Github Google Scholar. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, John Schulman, Emanuel Todorov, Sergey Levine University of Washington. -- These techniques have been implemented using 'R'. Assignments are done with jupyter using scikit learn. I am a PhD student in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, Seattle. Designed BI Warehouse and ETL Architectures, Performed Data Analysis, Business reporting in Oracle BI and implemented Data security protocols to name a few responsibilities. With skills from Warehousing, ETL, BI Architecture, Reporting and Analysis, I have it all in me. Machine learning plays a role in many deployed decision systems, often in ways that are difficult or impossible to understand by human stakeholders. Have also implemented prediction algorithms on datasets to understand them better. See LICENSE for further details. Course 1: Machine Learning Foundations: A Case Study Approach About me. About Me. STAT 538 (Winter 2019 & Winter 2020, UW): Statistical Learning: Modeling, Prediction, and Computing.
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