A ML/AI engineer, IT developer, IoT maker, system biologist, traveler, guitar player.
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ioutracker
May 10, 2020 – May 18, 2020
IOUTracker implements a tracking algorithm or method to track objects based on their Intersection-Over-Union (IOU) information across the consecutive frames.
View Projectdistributed_training
March 19, 2019 – November 11, 2020
This repository is a tutorial targeting how to train a deep neural network model in a higher efficient way. In this repository, we focus on two main frameworks that are Keras and Tensorflow.
View ProjectFlask_Video_Streaming_for_Object_Detection
December 19, 2018 – December 19, 2018
the simple example for object detection to the video streaming via flask server
View ProjectTF_ObjectDetection_Flow
May 10, 2018 – December 10, 2019
The tutorial is the workflow from labeling objects, building a object detection model in tensorflow, training it locally, and then using it on python.
View Projectscai
May 10, 2018 – May 21, 2018
Simple Cloud-AI (SCAI) is a simple Restful API server for AI image recognition.
View Projectvott
February 22, 2018 – April 27, 2018
This tool provides end to end support for generating datasets and validating object detection models from video and image assets. The generated output data would be further the input into the CNTK.
View ProjectFirstPersonController
December 18, 2017 – October 31, 2021
a tutorial for first person controller on unity
View Projectsophia
May 9, 2017 – April 1, 2022
The sophia project is the coding-based tutorial for machine intelligence (MI) and artificial intelligence (AI).
View ProjectNextGenerationSequencing
April 11, 2016 – November 8, 2016
Construct a flow to analyze NGS data based on R, Perl, and Python.
View ProjectCultural Fit Analysis
The candidate's projects are exclusively personal tutorials, which, while demonstrating technical initiative, do not provide insight into collaborative work environments or diverse project types typically found in a professional setting. The focus is heavily on individual technical exploration rather than team-oriented or business-driven solutions. This suggests a potential gap in understanding enterprise-level data science challenges and collaboration dynamics.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a strong focus on technical tutorials and implementations.