Ramon Qu's repositories
LI-FI-Arduino
Personal project, Low-level Visible Light communication system.
DietImprovement
Using Machine Learning in Hybrid Recommendation System for Diet Improvement Based on Health and Taste
wireless-data-transmission
current project in PRL, general approach for wireless data transmission from robot end-effectors
prl_wireless_perception
prl_wireless_perception
dive-into-machine-learning
Dive into Machine Learning with Python Jupyter notebook and scikit-learn!
feature-engineering
An example of feature engineering using bike data
gatsby-themes
Get high-quality and customizable Gatsby themes to quickly bootstrap your website! Choose from many professionally created and impressive designs with a wide variety of features and customization options.
graduation
$ git remote <graduation> yearbook
info-201-a7
info-201-a7 data Report Project
info-201-final
info-201-final-project
installROSTX2
Install Robot Operating System (ROS) on NVIDIA Jetson TX2
jetson-scripts
Configuration scripts and install guides for NVIDIA Jetson platform
librealsense
Intel® RealSense™ SDK
ramonidea.github.io
Personal Website
robotics-toolbox-python
Robotics Toolbox for Python
ssd.pytorch
A PyTorch Implementation of Single Shot MultiBox Detector
Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
TeensyStep
Fast Stepper Motor Library for Teensy boards
Text-Classification-Pytorch
Text classification using deep learning models in Pytorch