Framework that uses artificial intelligence applied to mathematical models to make predictions

Related tags

Deep LearningLiconIA
Overview

LiconIA

Framework that uses artificial intelligence applied to mathematical models to make predictions

GitHub Release GitHub license


Interface Overview

image

Table of contents

[TOC]


1 Articles, theses for technical support

1.1 Final Coursework



1.2 Dissertation



1.3 Theses


loading...


1.4 Articles



2 Requirements


  • Python 3.6 or superior (sudo apt-get install python3.6 under Linux)
  • Python virtual environment (sudo apt-get install python3.6-venv under Linux)

3 Package structure (need to update)


The initial directory structure should look like this:


4 Development and Tests

4.1 Installing the package


Start by creating a new virtual environment for your project. Next, update the packages pip and setuptools to the latest version. Then install the package itself.

$ sudo apt-get install python3-tk
$ /usr/bin/python3.6 -m venv --prompt="LiconIA" venv
$ source venv/bin/activate
(LiconIA) $ pip install --upgrade setuptools pip
(LiconIA) $ pip install numpy matplotlib pandas xlrd PyQt5
(LiconIA) $ pip install xlrd==1.2.0

4.2 Run program


To run the code just type:

$ python run.py

4.3 Qt-desing Information


Information about running the interface in qt-desing https://pythonbasics.org/qt-designer-python/

How to start Designer

$ cd /usr/lib/x86_64-linux-gnu/qt5/bin/ && ./designer
$ ./designer

Information about widgets the interface in qt-desing https://doc.qt.io/qtforpython/PySide2/QtWidgets/

Convert ui to py

pyuic5 /home/linux/helloworld.ui -o helloworld.py

4.4 Code checking


It is also possible to check for errors in Python code using:

use a pep8 -> pycodestyle


4.5 Development Team



5 License


This package is released and distributed under the license GNU GPL Version 3, 29 June 2007.

Semi-supervised Learning for Sentiment Analysis

Neural-Semi-supervised-Learning-for-Text-Classification-Under-Large-Scale-Pretraining Code, models and Datasets for《Neural Semi-supervised Learning fo

47 Jan 01, 2023
1st Solution For ICDAR 2021 Competition on Mathematical Formula Detection

This project releases our 1st place solution on ICDAR 2021 Competition on Mathematical Formula Detection. We implement our solution based on MMDetection, which is an open source object detection tool

yuxzho 94 Dec 25, 2022
Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at [email protected]

TableParser Repo for "TableParser: Automatic Table Parsing with Weak Supervision from Spreadsheets" at DS3 Lab 11 Dec 13, 2022

A Kitti Road Segmentation model implemented in tensorflow.

KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark

Marvin Teichmann 890 Jan 04, 2023
Deep generative models of 3D grids for structure-based drug discovery

What is liGAN? liGAN is a research codebase for training and evaluating deep generative models for de novo drug design based on 3D atomic density grid

Matt Ragoza 152 Jan 03, 2023
Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation

Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation

NVIDIA Research Projects 4.8k Jan 09, 2023
Adaptable tools to make reinforcement learning and evolutionary computation algorithms.

Pearl The Parallel Evolutionary and Reinforcement Learning Library (Pearl) is a pytorch based package with the goal of being excellent for rapid proto

38 Jan 01, 2023
scAR (single-cell Ambient Remover) is a package for data denoising in single-cell omics.

scAR scAR (single cell Ambient Remover) is a package for denoising multiple single cell omics data. It can be used for multiple tasks, such as, sgRNA

19 Nov 28, 2022
An algorithmic trading bot that learns and adapts to new data and evolving markets using Financial Python Programming and Machine Learning.

ALgorithmic_Trading_with_ML An algorithmic trading bot that learns and adapts to new data and evolving markets using Financial Python Programming and

1 Mar 14, 2022
Educational 2D SLAM implementation based on ICP and Pose Graph

slam-playground Educational 2D SLAM implementation based on ICP and Pose Graph How to use: Use keyboard arrow keys to navigate robot. Press 'r' to vie

Kirill 19 Dec 17, 2022
Implementation of PyTorch-based multi-task pre-trained models

mtdp Library containing implementation related to the research paper "Multi-task pre-training of deep neural networks for digital pathology" (Mormont

Romain Mormont 27 Oct 14, 2022
AoT is a system for automatically generating off-target test harness by using build information.

AoT: Auto off-Target Automatically generating off-target test harness by using build information. Brought to you by the Mobile Security Team at Samsun

Samsung 10 Oct 19, 2022
An experimental technique for efficiently exploring neural architectures.

SMASH: One-Shot Model Architecture Search through HyperNetworks An experimental technique for efficiently exploring neural architectures. This reposit

Andy Brock 478 Aug 04, 2022
The object detection pipeline is based on Ultralytics YOLOv5

AYOLOv2 The main goal of this repository is to rewrite the object detection pipeline with a better code structure for better portability and adaptabil

153 Dec 22, 2022
VOLO: Vision Outlooker for Visual Recognition

VOLO: Vision Outlooker for Visual Recognition, arxiv This is a PyTorch implementation of our paper. We present Vision Outlooker (VOLO). We show that o

Sea AI Lab 876 Dec 09, 2022
IEEE-CIS Technical Challenge on Predict+Optimize for Renewable Energy Scheduling

IEEE-CIS Technical Challenge on Predict+Optimize for Renewable Energy Scheduling This is my code, data and approach for the IEEE-CIS Technical Challen

3 Sep 18, 2022
Guiding evolutionary strategies by (inaccurate) differentiable robot simulators @ NeurIPS, 4th Robot Learning Workshop

Guiding Evolutionary Strategies by Differentiable Robot Simulators In recent years, Evolutionary Strategies were actively explored in robotic tasks fo

Vladislav Kurenkov 4 Dec 14, 2021
Small utility to demangle Nim symbols in callgrind files

nim_callgrind A small utility to demangle Nim symbols from callgrind files. Usage Run your (Nim) program with something like this: valgrind --tool=cal

kraptor 3 Feb 15, 2022
Differentiable rasterization applied to 3D model simplification tasks

nvdiffmodeling Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Automatic 3D Model

NVIDIA Research Projects 336 Dec 30, 2022
A bunch of random PyTorch models using PyTorch's C++ frontend

PyTorch Deep Learning Models using the C++ frontend Gettting started Clone the repo 1. https://github.com/mrdvince/pytorchcpp 2. cd fashionmnist or

Vince 0 Jul 13, 2021