-- First graph shows top Batsman performance from both the teams, second shows the team results of all the series and the Contribute to tuanavu/coursera-university-of-washington development by creating an account on GitHub. As a Data Science for Social Good fellow at the University of Chicago in 2015, I helped develop the Legislative Influence Detector. Machine-Learning-University-of-Washington My machine learning projects about regression, classification and clustering All projects are completed using Pandas, Numpy, Scikit-learn and matplotlib. 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. All Solutions licensed under MIT License. With skills from Warehousing, ETL, BI Architecture, Reporting and Analysis, I have it all in me. I am a PhD student in the Paul G. Allen School of Computer Science and Engineering at the University of Washington, Seattle. -- Visualization provides a backdrop into energy consumption in the US and the comparison between the various types of bulbs. This repository contains 15 homeworks of Machine Learning course of National Taiwan University (NTU). STAT 538 (Winter 2019 & Winter 2020, UW): Statistical Learning: Modeling, Prediction, and Computing. MATH 394 (Winter 2021, UW): Probability I. STAT 516 (Autumn 2020, UW): Stochastic Modeling. Designed BI Warehouse and ETL Architectures, Performed Data Analysis, Business reporting in Oracle BI and implemented Data security protocols to name a few responsibilities. My Forte. ... Graduate School: University of Washington. Online Meta-Learning Chelsea Finn, Aravind Rajeswaran, Sham Kakade, Sergey Levine International Conference on Machine Learning (ICML) 2019; arXiv:1902.08438. -- Perfomed a twitter sentiment analysis on live stream data using Twitter API. He received his Ph.D. in Electrical & Computer Engineering (ECE) from the University of Washington (UW) in 2019, and his B.S. Kunal Seth - Blending Data and Creativity at Adobe. See LICENSE for further details. My research focuses on pure exploration multi-armed bandits, recommender systems, and nonparametric estimation. Machine learning — the ability for computers to detect patterns in data and use it to make predictions — is changing our world in profound ways. -- Designed multiple filters to narrow down search by Country, Region, Income Group, Year and Population. With an experience of around 4 years in the BI space, I am one of the best you can get. Founded in 1861, the University of Washington is one of the oldest state-supported institutions of higher education on the West Coast and is one of the preeminent research universities in the world. The field of data motivated me to delve further into it and I decided to pursue my Masters in Information Management with a focus on Data Science and Business Intelligence. As the technology becomes faster and more accessible, machine learning is sparking innovations big and small, from customer service chatbots to … Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. Graduate student in Atmospheric Sciences researching applications of machine learning to ensemble weather forecasting. I earned my PhD studying Machine Learning as a student of Prof. Sham M. Kakade at the University of Washington Seattle. Rahul Kidambi . ... 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. Supervised learning and predictive modeling: decision trees, rule induction, nearest neighbors, Bayesian methods, neural networks, support vector machines, and model ensembles. For all the other courses (Regression, Classification and Clustering) I have used pandas for feature enginering and … Working as a Data Insights Manager on Lightroom Ecosystem delivering the best of data driven applications and helping to nurture creativity for our customers. If nothing happens, download the GitHub extension for Visual Studio and try again. Biography. Learn more. I was a teaching assistant for. ... Machine Learning: License. I like the interior decoration and the blackboard menu on the wall. University of Washington. -- Different tabs on the story explore different dimensions. -- Created a visualization in D3 to explore the relationship between World Employment vs Internet usage in various countries. If nothing happens, download Xcode and try again. -- Conducted a survey to analyze the current understanding of the users for home lighting. Use Git or checkout with SVN using the web URL. Prior to that, I received my B.S. Explaining, in a human-understandable way, the relationship between the input and output of machine learning models is essential to the development of trustworthy machine-learning-based systems. If nothing happens, download GitHub Desktop and try again. If nothing happens, download GitHub Desktop and try again. Techniques used: Python, pandas, numpy,scikit-learn, graphlab. O’Reilly Media, Inc. O’Reilly Media, Inc. Goldstein, Alex, Adam Kapelner, Justin Bleich, and Emil Pitkin. 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 I am also excited about optimal transport and its applications in statistics and machine learning. I am an Assistant Professor of Machine Learning at MILA (Quebec Institute for Learning Algorithms)/HEC Montréal (U. Montreal’s business school). In terms of the library and packages, I only used graphlab and SFrame for Machine Learning Foundations. 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. See LICENSE for further details. I am a post-doctoral researcher in the department of Computer Science at Cornell University. Work fast with our official CLI. All incoming and current students are eligible to apply. Explain how neural networks (deep and otherwise) compare to other machine learning models. -- Exploratory data analysis has been performed on the murder statistics of 2012 in the United States. I have studied Statistical Machine Learning. -- Python code to extract tweet sentiment, term frequency, top hashtags, happiest US State on live tweets. MISC Teaching. My skills include Oracle BI (10G/11G), Microsoft SQL stack, Informatica, SSIS and Hive to name a few. This course is designed to fill this gap. Stanford’s Machine Learning by Andrew Ng; University of Washington’s Machine Learning Specialization; fast.ai; MITx’s Machine Learning with Python: From Linear Models to Deep Learning; StatQuest’s Machine Learning Series; Machine Learning Nanodegree Program by Udacity; Reinforcement Learning by Udacity Machine learning plays a role in many deployed decision systems, often in ways that are difficult or impossible to understand by human stakeholders. Programming Assignments for machine learning specialization courses from University of Washington through Coursera. -- The visualization created in Tableau shows how Australia and England players have performed in the historic Ashes Test Series. Dr. Brunton's research focuses on combining techniques in dimensionality reduction, sparse sensing, and machine learning for the data-driven discovery and control of complex dynamical systems. Preprints Contribute to drbaguiar/Machine-Learning-Specialization-University-of-Washington- development by creating an account on GitHub. Currently pursuing the Data Science specialization at the UW. This repo contains lectures and assignments of University of Washington - Coursera. -- Captured raw data from 2010 to 2014 and cleaned it to make it visualization ready. Machine Learning courses. CSE446: Machine Learning. Acting Assistant Professor, Applied Mathematics, University of Washington, 2012–2014; Research Statement. Here is my resume (as of January 2019) You can also find me on: LinkedIn Github Google Scholar. Tutorial on Optimal Transport in Computational Neuroscience, Neurohackademy, 2020.. -- Created a application in D3.js to help users decide lighting for their homes. in mathematics and applied mathematics at Tsinghua University. About me. 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. I am broadly interested in safe and interpretable machine learning with applications in natural language processing. 2015. 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. third one shows how top Bowlers have performed over the years. Coursera Assignment and Project. Have also implemented prediction algorithms on datasets to understand them better. Skills include: R, SQL, Python, Javascript, D3, HTML. Previously, I was a postdoctoral fellow in the NSF-TRIPODS institute ADSI (now IFDS) at the University of Washington.. Working as a Business Intelligence Consultant, I lead my team through different projects and churning through data for 3 years. I am also interested in applications of machine learning that promote the social good. Learn, Implement, Repeat. -- Refer the documents via the link for detailed analysis of the techniques and datasets used. My research interests include natural language processing, semantic role labeling, multimodal learning for vision and language, and machine learning applications. Catalog Description: Methods for designing systems that learn from data and improve with experience. - Offliners/NTUML2021_Hung-yi-Lee Graduated in June 2017 with a bag full of Dataskills. -- Implemented different Machine Learning Algorithms on different datasets. download the GitHub extension for Visual Studio. -- These techniques have been implemented using 'R'. 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. 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. Hands-on Machine Learning with Scikit-Learn and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems. There are 4 courses in the Machine Learning Specialization provided by University of Washington via Coursera. We will be covering various aspects of deep learning systems, including: basics of deep learning, programming models for expressing machine learning models, automatic differentiation, memory optimization, scheduling, distributed learning, hardware acceleration, domain specific languages, and model serving. Assignments are done with jupyter using scikit learn. SAMPL is an interdisciplinary machine learning research group exploring problems spanning multiple layers of the system stack including deep learning frameworks, specialized hardware for training and inference, new intermediate representations, differentiable programming, and various applications. Clone via HTTPS Clone with Git or checkout with SVN using the repository’s web address. -- Scalable code to run on any twitter dataset. Determine when a deep neural network would be a good choice for a particular problem. Fond of data, I was motivated to take up a job in this field. My wife tried their ramen and it was pretty forgettable. I am interested in exploring ways to make Machine Learning trustworthy. About Me. Hello! -- Multiple graphs designed in order to explore and visualize the safe and unsafe states with respect to Murder stats. I have explored explainability and fairness aspects of Machine Learning to make it … • CV • Github • Scholar contact: rkidambi AT cornell DOT edu This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Oracle Certified SQL Expert and Oracle Certified DBA. Statistics and Machine Learning. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations Aravind Rajeswaran, Vikash Kumar, Abhishek Gupta, John Schulman, Emanuel Todorov, Sergey Levine All Solutions licensed under MIT License. You signed in with another tab or window. I am currently a PhD student at the University of Washington, advised by Su In Lee.I am interested in developing methods to make machine learning models more interpretable, and applying such methods to understand biological and health data. jweyn@uw.edu. Optimizing Distributed Systems using Machine Learning phd thesis Ignacio Cano Paul G. Allen School of Computer Science & Engineering, University of Washington, 2019 Course 1: Machine Learning Foundations: A Case Study Approach About this Specialization. Use Git or checkout with SVN using the web URL. Course Materials I am an acting instructor in the Department of Statistics at the University of Washington.. Research. University of Washington - Machine learning - Regression - k-fold-ridge.r. Intern at Point B in Seattle as a Business Intelligence developer helping the team set up an end-to-end BI system which will help the business perform self service BI and personalized data analysis. 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 My first hands on real data. Demonstrate your understanding of the material through a final project uploaded to GitHub. Contribute to tuanavu/coursera-university-of-washington development by creating an account on GitHub. If nothing happens, download GitHub … The UW Department of Statistics now offers a PhD track in the area of Machine Learning and Big Data. Publications. Bio. PhD Student in Machine Learning.

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