Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.

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Deep LearningCodes-for-Algorithms
Overview

Codes-for-Algorithms

  • Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.
  • Upload on a random basis.
  1. Junior Data Processing
  • Calculate Distance N dimensional vector:
    • euclidean
    • manhattan
    • Minkowski
  • Calculate Similarity:
    • Jaccard
    • Simple Matching Coefficent(SMC)
  • Calculate relevance:
    • Covariance
    • Sample Standard Deviation (ssd)
    • Pearson Coeffiencent
  • Apriori
  • FPGrowth
Owner
Tracy (Shengmin) Tao
STEM girl in business world.
Tracy (Shengmin) Tao
GitHub Repository
Mail classification with tensorflow and MS Exchange Server (ham or spam).

Mail classification with tensorflow and MS Exchange Server (ham or spam).

Metin Karatas 1 Sep 11, 2021
Seach Losses of our paper 'Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search', accepted by ICLR 2021.

CSE-Autoloss Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models

Peidong Liu(εˆ˜ζ²›δΈœ) 54 Dec 17, 2022
Breast Cancer Detection πŸ”¬ ITI "AI_Pro" Graduation Project

BreastCancerDetection - This program is designed to predict two severity of abnormalities associated with breast cancer cells: benign and malignant. Mammograms from MIAS is preprocessed and features

6 Nov 29, 2022
Code for the Weighted, Accelerated and Restarted Primal-dual algorithm. This algorithm achieves stable linear convergence for reconstruction from undersampled noisy measurements under an approximate sharpness condition. See the paper for details.

WARPd Code for the Weighted, Accelerated and Restarted Primal-dual algorithm. This algorithm achieves stable linear convergence for reconstruction fro

Matthew Colbrook 1 Apr 08, 2022
Pmapper is a super-resolution and deconvolution toolkit for python 3.6+

pmapper pmapper is a super-resolution and deconvolution toolkit for python 3.6+. PMAP stands for Poisson Maximum A-Posteriori, a highly flexible and a

NASA Jet Propulsion Laboratory 8 Nov 06, 2022
Embodied Intelligence via Learning and Evolution

Embodied Intelligence via Learning and Evolution This is the code for the paper Embodied Intelligence via Learning and Evolution Agrim Gupta, Silvio S

Agrim Gupta 111 Dec 13, 2022
Code and model benchmarks for "SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology"

NeurIPS 2020 SEVIR Code for paper: SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology Requirement

USAF - MIT Artificial Intelligence Accelerator 46 Dec 15, 2022
Subpopulation detection in high-dimensional single-cell data

PhenoGraph for Python3 PhenoGraph is a clustering method designed for high-dimensional single-cell data. It works by creating a graph ("network") repr

Dana Pe'er Lab 42 Sep 05, 2022
MINOS: Multimodal Indoor Simulator

MINOS Simulator MINOS is a simulator designed to support the development of multisensory models for goal-directed navigation in complex indoor environ

194 Dec 27, 2022
The code for "Deep Level Set for Box-supervised Instance Segmentation in Aerial Images".

Deep Levelset for Box-supervised Instance Segmentation in Aerial Images Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu* This code is based on MMdetecti

sunshine.lwt 112 Jan 05, 2023
ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts

ANEA The goal of Automatic (Named) Entity Annotation is to create a small annotated dataset for NER extracted from German domain-specific texts. Insta

Anastasia Zhukova 2 Oct 07, 2022
Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals

LapDepth-release This repository is a Pytorch implementation of the paper "Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals" M

Minsoo Song 205 Dec 30, 2022
Awesome Graph Classification - A collection of important graph embedding, classification and representation learning papers with implementations.

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

Benedek Rozemberczki 4.5k Jan 01, 2023
Lightweight library to build and train neural networks in Theano

Lasagne Lasagne is a lightweight library to build and train neural networks in Theano. Its main features are: Supports feed-forward networks such as C

Lasagne 3.8k Dec 29, 2022
Pytorch based library to rank predicted bounding boxes using text/image user's prompts.

pytorch_clip_bbox: Implementation of the CLIP guided bbox ranking for Object Detection. Pytorch based library to rank predicted bounding boxes using t

Sergei Belousov 50 Nov 27, 2022
Official PyTorch implementation for "Low Precision Decentralized Distributed Training with Heterogenous Data"

Low Precision Decentralized Training with Heterogenous Data Official PyTorch implementation for "Low Precision Decentralized Distributed Training with

Aparna Aketi 0 Nov 23, 2021
UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model

UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Model Official repository for the ICCV 2021 paper: UltraPose: Syn

MomoAILab 92 Dec 21, 2022
Open-Domain Question-Answering for COVID-19 and Other Emergent Domains

Open-Domain Question-Answering for COVID-19 and Other Emergent Domains This repository contains the source code for an end-to-end open-domain question

7 Sep 27, 2022
PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis

Impersonator PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer an

SVIP Lab 1.7k Jan 06, 2023
Adjusting for Autocorrelated Errors in Neural Networks for Time Series

Adjusting for Autocorrelated Errors in Neural Networks for Time Series This repository is the official implementation of the paper "Adjusting for Auto

Fan-Keng Sun 51 Nov 05, 2022