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$50/h
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Response Time 1h
Lessons offered by Yuan
  • Individual
The lessons will be held
Taught subjects
  • Computer networks
  • Network
  • Information security
  • Telecommunications
  • Machine learning
  • Coding
Levels
  • All Levels

Computer engineer student give programming, algorithm, computer network classes in vancouver, university level or high school level.

Methodology

My teaching methodology is descriptive, heuristic, and interesting, catered to your need and your questions. I like to summarize the key points and concepts for a course. And when you don't understand some concepts I can explain and also tell you how to apply the method to similar types of problems.

Background

I am a master student in computer engineering, having python software development experience, machine learning experience, data structure and algorithm experience. I am a very orientated, patient and good at python programming. Having a solid background in electrical and computer engineering and working experience in software development.

Rates

Rate for online lessons : $ 50/h
Lessons offered by Yuan
Individual
The lessons will be held
Taught subjects
  • Computer networks
  • Network
  • Information security
  • Telecommunications
  • Machine learning
  • Coding
Levels
  • All Levels

Yuan's Resume

Master of Engineering – Electrical and Computer Engineering.
• Successful Participant, Mathematical Contest in Modeling Jan.2017
• Traffic control technology Co. Scholarship (Top1%), Beijing Jiaotong University Oct.2016
• First Class Scholarship (Top 3%), Beijing Jiaotong University Oct.2015
SOFTWARE DEVELOPMENT EXPERIENCE
Videx(online learning platform) annotation sharing feature implementation May-Aug.2020
(Tech stack: Typescript, React, Redux, ExpressJS, NodeJS, Webpack, Docker, Jenkins)
• Enhanced user experience by designing and implementing annotation sharing feature on the existing well-established code base, which showed 90% user experience improvement.
• Followed the React-Redux code best practice and created the annotation sharing user interface, which included rendering components when clicking on certain buttons, calling backend API in frontend actions, fetching Redux store state across different React-Redux components.
• Created REST API in the backend and created a new table in MongoDB to store sharing information, reference other tables, perform POST, GET requests.
• Designed the method of frontend React-Redux objects calling the Express.js backend API for the frontend to effectively communicate to the backend.

Comparison and evaluation of Android automated testing tools Jan – Apr.2020
• Created automated Python scripts for the project, including executing automated testing tools, collecting coverage data per minute, calculate accumulate coverage, generating graphs.
• Compared the testing coverage difference between classical and state-of-the-art automation testing tools, including method, basic block, class coverage, on five different Android apps.
• Reported on the suitable scenarios and limitations for each automated testing tool.

MACHINE LEARNING SOFTWARE DEVELOPMENT EXPERIENCE
Machine learning application on water quality parameters prediction Jan – Apr.2020
• Took major coding responsibility of the project and coordinated with domain expert in the analysis.
• Researched for and implemented regression methods, including polynomial regression, xgboost, etc.
• Built and tuned artificial neural network and radial basis function net for regression using Keras.
• Improved the recognition accuracy to 99% by making modifications to traditional radial basis function network.

Reinforcement learning in Robocode Tank Sept - Dec.2018
• Implemented using both Look-Up-Table and deep neural network for reinforcement learning tank.
• Developed a robot tank in Robocode(a game in JAVA) using reinforcement learning and improved its winning rate to 98% during battles.

Automatic instrument recognition based on multi-instance learning Mar - Jun.2018
• Conducted a thorough research on existing applications of multi-instance learning on image recognition.
• Implemented SVM, HOG, PCA algorithms on the problem and compared their performance.
• Designed a modified multi-instance learning model to recognize indicator lights and rotary knob positions automatically, which outperformed traditional methods and improved the accuracy of recognition to 99%.

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