In this workshop, we will talk about deep learning and neural network from a different perspective. After a very brief introduction to what machine learning and deep learning are, our discussion will be focused on what deep learning technology can (and cannot) bring to academic research, including both the benefits and the challenges. No specific…
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Machine Learning
Introduction to Neural Networks
This workshop is a descriptive “no-math” and “no-python” introduction to what deep learning is and how to train a deep neural network. Our discussion will be arranged along with a general procedure for working on a deep learning project. Basic knowledge of calculus and linear algebra will be helpful in understanding the details. Any questions…
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High Performance Machine Learning Using Scikit-Learn
As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will discuss some advanced topic on using scikit-learn python library to make high performance machine learning, specifically the speedup modeling using multicore and…
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Learning Scikit-Learn
As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will present an introduction about the basics of scikit-learn python library. Prerequisite knowledge for the workshop includes Python programming and basic machine learning…
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Learning Convolutional Neural Networks (2)
Workshop will be conducted in Zoom in PST time. Please Register here in advance for this lecture. This workshope will be the second lecture on the introduction to convolutional neural network. We will continue our learning on how to apply data augmentation and transfer learning techniques to get a better solution for the classic Dogs-vs-Cats…
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Learning Convolutional Neural Networks (1)
Workshop will be conducted in Zoom in PST time. Please Register here in advance for this lecture. This workshope will be an introduction on convolutional neural network. We will start our learning on how to use PyTorch to do image processing for classic Dogs-vs-Cats problem. The knowledge of topics covered in the previous sessions is…
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High Performance Machine Learning Using Scikit-Learn
As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will discuss some advanced topic on using scikit-learn python library to make high performance machine learning, specifically the speedup modeling using multicore and accelerators and out-of-core learning. The session assumes the knowledge of topics covered in the first session. Working experience on Python programming, basic machine learning concepts and Scikit-learn will be helpful.
Learning Scikit-Learn: the basics
As machine learning gains more and more popularity in science and technology in recent years, scikit-learn becomes one of the must-have libraries in the general machine learning toolbox. In this lecture we will present an introduction about the basics of scikit-learn python library. Prerequisite knowledge for the workshop includes Python programming and basic machine learning concepts.
Professor receives AWS award for machine learning research
Quanquan Gu, an assistant professor of computer science at the UCLA Samueli School of Engineering, was awarded the Amazon Web Services (AWS) Machine Learning Research Award. Since 2017, these quarterly awards are granted to faculty, doctoral candidates and graduate students who research create open source tools and contribute to the machine learning community. Gu’s statistical…
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Exploring Data and Machine Learning with Interactive Python Tools
This course will teach attendees how to build interactive widgets and visualizations for exploring equations, datasets, and machine learning models. This course will touch on several machine learning tools in Python, but the primary goal will be to give attendees a foundation in tools that can be useful in exploring datasets and conceptualizing models. Basic…
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