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accelerated-computing-with-cuda-python

accelerated-data-science-with-rapids

adelaidet

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

ai_self-driving-car

Extensive study and research on Udacity Self-driving Car Challenge 2

byol-pytorch

Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch

cdp_edith

This is a Team D's final project for Capstone Design Project course at Sungkyunkwan University (Fall 2021).

chingisooinar.github.io

This is for my course assignment

clustering-my-songs-on-spotify

Exploring Audio Features, classifying into moods and building a Machine Learning Approach

cosmos-generation

deep-learning-notes

Notes from the DeepLearning.AI courses

deploying-a-sentiment-analysis-model

The notebook and Python files provided here, once completed, result in a simple web app which interacts with a deployed recurrent neural network performing sentiment analysis on movie reviews. This project assumes some familiarity with SageMaker, the mini-project, Sentiment Analysis using XGBoost, should provide enough background

detectron2

Detectron2 is FAIR's next-generation platform for object detection and segmentation.

end-to-end-deep-learning-approach-for-autonomous-driving-duckietown

This work is a Pytorch and Keras implementation of NVIDIA's DAVE-2 architecture used on DuckieTown simulator.

facenet

Face recognition using Tensorflow

facial-landmarks-detection

The project is a solution for Kaggle Facial Keypoints Detection problem using CNN. The project can also be easily adapted for YouTube Faces With Facial Keypoints dataset.

githubgraduation-2022

Join the GitHub Graduation Yearbook and "walk the stage" on June 11.

introduction-to-attention

isda-for-deep-networks

An efficient implicit semantic augmentation method, complementary to existing non-semantic techniques.

k-means-image-compression

This project is an introduction to K-means clustering through its Python implementation. Also, it includes its application to image compression.

knn-python-implementation

K-Nearest Neighbours is considered to be one of the most intuitive machine learning algorithms since it is simple to understand and explain. Additionally, it is quite convenient to demonstrate how everything goes visually. However, the kNN algorithm is still a common and very useful algorithm to use for a large variety of classification problems. If you are new to machine learning, make sure you test yourself on an understanding of both of this simple yet wonderful algorithm.

kotlin-basic-syntax-into-java-translator

The program translates the basic Kotlin Syntax into a Java code. Kotlin.g4 is a grammar written using antl4 that accepts a code written in Kotlin, while Kotlin2Java.java converts the code using rules specified. However, it does not handle String templates.

leetcode

leetcode-questions-by-company

A list of LeetCode questions with the corresponding companies

metric-transfer.pytorch

Deep Metric Transfer for Label Propagation with Limited Annotated Data

mlnd-capstone-project

This is a Capstone Project for my Machine Learning Nanodegree at Udacity. The problem of the project is a Satellite to Map Image Translation using conditional GAN.

mmselfsup

OpenMMLab Self-Supervised Learning Toolbox and Benchmark

moco

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

neural-style-algorithm.pytorch

The implementation of Neural Style algorithm using Pytorch.

neuralnetworksfromscratch

This repository contains my practice codes based on the book "Neural Networks From Scratch".

object-detection_from-scratch