No Code AI/ML platform

Overview

NoCodeAIML

No Code AI/ML platform - Community Edition

Watch the video credits: Uday Kiran

Video credits: Uday Kiran

Typical No Code AI/ML Platform will have features like drag and drop, data source connectivity, social media analysis, analytics, and content analysis.No code AI/ML platform can be built using python and streamlit, which helps in images analysis. The analytical data in the no-code AI/ML platform is imported, validated, cleansed, trained, and testing of the model. New scenarios come in due to unseen data and the model is refined for predictive analytics.

Planning to add more features, please contribute.

check out my article on AI4 blog No Code AI/ML Platform

alt text

Use Cases

1.analyze text messages
2.classify shipping documents
3.categorize social media pictures
4.categorize Instagram pictures
5.check onboarding documents
6.categorize startups by description
7.filter startup databases for investment decisions
8.categorizing emails
9.tracking keyword engagement
10.social listening
11.categorizing app crash reports using NLP
12.moderate user-generated content
13.insurance claims identification
14.quality inspection
15.auto-tagging real estate images,
16.tagging email attachments
17.categorizing support tickets
18.analyze text responses of surveys
19.track social sentiments
20.categorizing SMS responses
21.recognize shipping documents

Features

1.Data Visualization
2.Data Analysis
3.Machine Learning Algorithms
4.Image Analysis
5.NLP & NLU
6.WebRTC API
7.Drawing API
8.Grids for tables

Instructions for setting up locally - webapp

  1. Ensure that python3 and streamlit

2.git clone this repository

git clone https://github.com/bhagvank/NoCodeAIML.git

  1. Install the required packages
pip3 install -r requirements.txt
  1. Run streamlit
streamlit run main.py
Owner
Bhagvan Kommadi
Bhagvan founded Quantica Computacao, the first quantum computing startup in India.
Bhagvan Kommadi
Container : Context Aggregation Network

Container : Context Aggregation Network If you use this code for a paper please cite: @article{gao2021container, title={Container: Context Aggregati

AI2 47 Dec 16, 2022
PyTorch implementation of PP-LCNet

PP-LCNet-Pytorch Pre-Trained Models Google Drive p018 Accuracy Models Top1 Top5 PPLCNet_x0_25 0.5186 0.7565 PPLCNet_x0_35 0.5809 0.8083 PPLCNet_x0_5 0

24 Dec 12, 2022
Pyramid Scene Parsing Network, CVPR2017.

Pyramid Scene Parsing Network by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page. Introduction This

Hengshuang Zhao 1.5k Jan 05, 2023
A general-purpose encoder-decoder framework for Tensorflow

READ THE DOCUMENTATION CONTRIBUTING A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summariz

Google 5.5k Jan 07, 2023
Meta Learning Backpropagation And Improving It (VSML)

Meta Learning Backpropagation And Improving It (VSML) This is research code for the NeurIPS 2021 publication Kirsch & Schmidhuber 2021. Many concepts

Louis Kirsch 22 Dec 21, 2022
Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

J K Terry 32 Nov 09, 2021
CS550 Machine Learning course project on CNN Detection.

CNN Detection (CS550 Machine Learning Project) Team Members (Tensor) : Yadava Kishore Chodipilli (11940310) Thashmitha BS (11941250) This is a work do

yaadava_kishore 2 Jan 30, 2022
LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice,

LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and eval

Ahmet Erdem 691 Dec 23, 2022
Official Pytorch implementation of the paper: "Locally Shifted Attention With Early Global Integration"

Locally-Shifted-Attention-With-Early-Global-Integration Pretrained models You can download all the models from here. Training Imagenet python -m torch

Shelly Sheynin 14 Apr 15, 2022
Small-bets - Ergodic Experiment With Python

Ergodic Experiment Based on this video. Run this experiment with this command: p

Michael Brant 3 Jan 11, 2022
L-Verse: Bidirectional Generation Between Image and Text

Far beyond learning long-range interactions of natural language, transformers are becoming the de-facto standard for many vision tasks with their power and scalabilty

Kim, Taehoon 102 Dec 21, 2022
Fast sparse deep learning on CPUs

SPARSEDNN **If you want to use this repo, please send me an email: [email pro

Ziheng Wang 44 Nov 30, 2022
AgML is a comprehensive library for agricultural machine learning

AgML is a comprehensive library for agricultural machine learning. Currently, AgML provides access to a wealth of public agricultural datasets for common agricultural deep learning tasks.

Plant AI and Biophysics Lab 1 Jul 07, 2022
PyElecCL - Electron Monte Carlo Second Checks

PyElecCL Python program to perform second checks for electron Monte Carlo radiat

Reese Haywood 3 Feb 22, 2022
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2020

Phillip Lippe 1.1k Jan 07, 2023
Texture mapping with variational auto-encoders

vae-textures This is an experiment with using variational autoencoders (VAEs) to perform mesh parameterization. This was also my first project using J

Alex Nichol 41 May 24, 2022
MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets)

MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets) Using mixup data augmentation as reguliraztion and tuning the hyper par

Bhanu 2 Jan 16, 2022
Implementation of Online Label Smoothing in PyTorch

Online Label Smoothing Pytorch implementation of Online Label Smoothing (OLS) presented in Delving Deep into Label Smoothing. Introduction As the abst

83 Dec 14, 2022
Riemann Noise Injection With PyTorch

Riemann Noise Injection - PyTorch A module for modeling GAN noise injection based on Riemann geometry, as described in Ruili Feng, Deli Zhao, and Zhen

2 May 27, 2022
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.

Semantic Meshes A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model. Paper If you find this framework usefu

Florian 40 Dec 09, 2022