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algo_trading_project

Algorithmic trading

beginner-guide-to-detectron2

Original Detectron2 git: https://github.com/facebookresearch/detectron2 some code in this document is adpated from the originanl Detectron2 tutorial by Facebook Please set **Runtime to GPU** to start Follow the instructions on each cell block to run Detectron2 models on your own images. Detectron2 is an extremely powerful tool in computer vision, it has dozens of advanced models that allow different image processing requirements and can be used to establish custom datasets to train your own models. Feel free to email me if you have any questions : [email protected] Really glad that you are here! Enjoy! -Tracy

build-and-tune-cnn

Build your own CNN and visualize tuning hyperparameters

ece444-f2023--assignment1

self-evaluation assignment

ece444-f2023-lab1

edu-frontend

eigen-face

Using MATLAB to see eigenfaces by calculating the eigenvectors

exam-scheduler

A univerisy exam scheduler that ensures no exam overloading, over lapping for each and every student

finance-data-sentiment-analysis-nlp

finetuning-bert

front-end-design

gpt-engineer

Specify what you want it to build, the AI asks for clarification, and then builds it.

image-processing-command

image processing command in python, including inverting gray scale, rgb to gray scale and basic commands like cropping and rotating.

linear-regression-vs.-svm

Compare Linear Regression and SVM in simple classification tasks

llm-homeschool

matplotlib

matplotlib: plotting with Python

melnet

Implementation of "MelNet: A Generative Model for Audio in the Frequency Domain"

my_quiz

myleetcode

Repo to keep track of my leetcode practices

nest

neural-music

nlp-glove

Global Vector model built from scratch

optimized-graph-search-algorithm

optimized graph search algorithm (BFS,Bidirectional search, A*)

playing-around-with-rnn

quiz

second-order-optimizer

stock-price-prediction-using-gan

In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.

tracy

tracyqian0720.github.io

wassersteingan