An AI Assistant More Than a Toolkit

Overview

tymon

An AI Assistant More Than a Toolkit The reason for creating framework tymon is simple. making AI more like an assistant, helping us to complete daily AI tasks we want to accomplish, rather than just a tool. I prefer it to be interactive and "human".

Installation

pip install tymon

Example

Timeseries Assistant

instant a timeseries assistant object, and choose model, set datapath.

from tymon.assistant import TimeSeries
assistant_object = TimeSeries(model_name='LSTM',data_path='./international-airline-passengers.csv')
assistant_object.run() 

run the code you will get a window to set the parameters for model.
parameters_image
set parameters to what you want, click the start button to train the model.
train_process
you will get final model in ./ and its performance image.
result_image

Related Blog

基于tymon,无需搭建LSTM,航班人数预测

Owner
TymonXie
i will not try to pick the moon,i want the moon to come to me.
TymonXie
Arabic Car License Recognition. A solution to the kaggle competition Machathon 3.0.

Transformers Arabic licence plate recognition 🚗 Solution to the kaggle competition Machathon 3.0. Ranked in the top 6️⃣ at the final evaluation phase

Noran Hany 17 Dec 04, 2022
On the Adversarial Robustness of Visual Transformer

On the Adversarial Robustness of Visual Transformer Code for our paper "On the Adversarial Robustness of Visual Transformers"

Rulin Shao 35 Dec 14, 2022
SegNet-Basic with Keras

SegNet-Basic: What is Segnet? Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-wise Image Segmentation Segnet = (Encoder + Decoder)

Yad Konrad 81 Jun 30, 2022
Benchmarks for Model-Based Optimization

Design-Bench Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box

Brandon Trabucco 43 Dec 20, 2022
MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;

MoViNet-pytorch Pytorch unofficial implementation of MoViNets: Mobile Video Networks for Efficient Video Recognition. Authors: Dan Kondratyuk, Liangzh

189 Dec 20, 2022
Implicit Deep Adaptive Design (iDAD)

Implicit Deep Adaptive Design (iDAD) This code supports the NeurIPS paper 'Implicit Deep Adaptive Design: Policy-Based Experimental Design without Lik

Desi 12 Aug 14, 2022
Codebase for testing whether hidden states of neural networks encode discrete structures.

structural-probes Codebase for testing whether hidden states of neural networks encode discrete structures. Based on the paper A Structural Probe for

John Hewitt 349 Dec 17, 2022
[ACL-IJCNLP 2021] Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning

CLNER The code is for our ACL-IJCNLP 2021 paper: Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning CLNER is a

71 Dec 08, 2022
Pytorch code for our paper "Feedback Network for Image Super-Resolution" (CVPR2019)

Feedback Network for Image Super-Resolution [arXiv] [CVF] [Poster] Update: Our proposed Gated Multiple Feedback Network (GMFN) will appear in BMVC2019

Zhen Li 539 Jan 06, 2023
SpeechNAS Better Trade off between Latency and Accuracy for Large Scale Speaker Verification

SpeechNAS Better Trade off between Latency and Accuracy for Large Scale Speaker Verification

Wentao Zhu 24 May 20, 2022
Data and analysis code for an MS on SK VOC genomes phenotyping/neutralisation assays

Description Summary of phylogenomic methods and analyses used in "Immunogenicity of convalescent and vaccinated sera against clinical isolates of ance

Finlay Maguire 1 Jan 06, 2022
The first dataset on shadow generation for the foreground object in real-world scenes.

Object-Shadow-Generation-Dataset-DESOBA Object Shadow Generation is to deal with the shadow inconsistency between the foreground object and the backgr

BCMI 105 Dec 30, 2022
In this project we use both Resnet and Self-attention layer for cat, dog and flower classification.

cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.

3 Nov 23, 2022
Official code of "R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network."

R2RNet Official code of "R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network." Jiang Hai, Zhu Xuan, Ren Yang, Yutong Hao, Fengzhu

77 Dec 24, 2022
The official implementation of ICCV paper "Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds".

Box-Aware Tracker (BAT) Pytorch-Lightning implementation of the Box-Aware Tracker. Box-Aware Feature Enhancement for Single Object Tracking on Point C

Kangel Zenn 5 Mar 26, 2022
Fbone (Flask bone) is a Flask (Python microframework) starter/template/bootstrap/boilerplate application.

Fbone (Flask bone) is a Flask (Python microframework) starter/template/bootstrap/boilerplate application.

Wilson 1.7k Dec 30, 2022
LSTMs (Long Short Term Memory) RNN for prediction of price trends

Price Prediction with Recurrent Neural Networks LSTMs BTC-USD price prediction with deep learning algorithm. Artificial Neural Networks specifically L

5 Nov 12, 2021
Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

News! Aug 2020: v0.4.0 version of AlphaPose is released! Stronger tracking! Include whole body(face,hand,foot) keypoints! Colab now available. Dec 201

Machine Vision and Intelligence Group @ SJTU 6.7k Dec 28, 2022
Hard cater examples from Hopper ICLR paper

CATER-h Honglu Zhou*, Asim Kadav, Farley Lai, Alexandru Niculescu-Mizil, Martin Renqiang Min, Mubbasir Kapadia, Hans Peter Graf (*Contact: honglu.zhou

NECLA ML Group 6 May 11, 2021
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

BCMI 49 Jul 27, 2022