NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

Overview

zoofs Logo Header

NitroFE ( Nitro Feature Engineering )

Maintainability Rating Reliability Rating Security Rating <Sonarcloud quality gate> DOI Code style: black

NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.

Documentation

https://nitro-ai.github.io/NitroFE/

Installation

PyPi version

Using pip

Use the package manager to install NitroFE.

pip install NitroFE

Available feature domains

Time based Features

Time based Features

Indicator / windows / moving averages features are dependent on past values for calculation, e.g. a rolling window of size 4 is dependent on past 4 values.

While creating such features during training is quite straighforward , taking it to production becomes challenging as it would requires one to externally save past values and implement logic. Creating indicators becomes even more complex as they are dependent on several other differently sized window components.

NitroFE internally handles saving past dependant values, and makes feature creation hassle free. Just use first_fit=True for your initial fit

  • Jump right in for a handson Open In Colab

The Time based domain is divided into 'Moving average features', 'Weighted window features' and 'indicator based features'

Indicators based Features

Time based Features

NitroFe provides a rich variety of features which are inspired and translated from market indicators.

Moving average features

exponential_moving_feature

In statistics, a moving average (rolling average or running average) is a calculation to analyze data points by creating a series of averages of different subsets of the full data set. NitroFE provides an array of variety of moving averages type for you to utilize.

Weighted window Features

NitroFe provides easy to use functions to create specified weighted window featuresm and send custom operations as per your need

You might also like...
Official implementation of the paper:
Official implementation of the paper: "LDNet: Unified Listener Dependent Modeling in MOS Prediction for Synthetic Speech"

LDNet Author: Wen-Chin Huang (Nagoya University) Email: [email protected] This is the official implementation of the paper "LDNet

Time Dependent DFT in Tamm-Dancoff Approximation
Time Dependent DFT in Tamm-Dancoff Approximation

Density Function Theory Program - kspy-tddft(tda) This is an implementation of Time-Dependent Density Functional Theory(TDDFT) using the Tamm-Dancoff

Pacman-AI - AI project designed by UC Berkeley. Designed reflex and minimax agents for the game Pacman.
Pacman-AI - AI project designed by UC Berkeley. Designed reflex and minimax agents for the game Pacman.

Pacman AI Jussi Doherty CAP 4601 - Introduction to Artificial Intelligence - Fall 2020 Python version 3.0+ Source of this project This repo contains a

FID calculation with proper image resizing and quantization steps
FID calculation with proper image resizing and quantization steps

clean-fid: Fixing Inconsistencies in FID Project | Paper The FID calculation involves many steps that can produce inconsistencies in the final metric.

Regression Metrics Calculation Made easy for tensorflow2 and scikit-learn

Regression Metrics Installation To install the package from the PyPi repository you can execute the following command: pip install regressionmetrics I

Finite-temperature variational Monte Carlo calculation of uniform electron gas using neural canonical transformation.

CoulombGas This code implements the neural canonical transformation approach to the thermodynamic properties of uniform electron gas. Building on JAX,

torchsummaryDynamic: support real FLOPs calculation of dynamic network or user-custom PyTorch ops

torchsummaryDynamic Improved tool of torchsummaryX. torchsummaryDynamic support real FLOPs calculation of dynamic network or user-custom PyTorch ops.

HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events globally on daily to subseasonal timescales.

HeatNet HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events glob

Python project to take sound as input and output as RGB + Brightness values suitable for DMX

sound-to-light Python project to take sound as input and output as RGB + Brightness values suitable for DMX Current goals: Get one pixel working: Vary

Releases(zenodo_0.0.10)
Official implementation of NeuralFusion: Online Depth Map Fusion in Latent Space

NeuralFusion This is the official implementation of NeuralFusion: Online Depth Map Fusion in Latent Space. We provide code to train the proposed pipel

53 Jan 01, 2023
This is an official implementation for "Self-Supervised Learning with Swin Transformers".

Self-Supervised Learning with Vision Transformers By Zhenda Xie*, Yutong Lin*, Zhuliang Yao, Zheng Zhang, Qi Dai, Yue Cao and Han Hu This repo is the

Swin Transformer 529 Jan 02, 2023
Unofficial PyTorch implementation of Attention Free Transformer (AFT) layers by Apple Inc.

aft-pytorch Unofficial PyTorch implementation of Attention Free Transformer's layers by Zhai, et al. [abs, pdf] from Apple Inc. Installation You can i

Rishabh Anand 184 Dec 12, 2022
Unofficial PyTorch implementation of "RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving" (ECCV 2020)

RTM3D-PyTorch The PyTorch Implementation of the paper: RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving (ECCV 2020

Nguyen Mau Dzung 271 Nov 29, 2022
Official implementation of "Generating 3D Molecules for Target Protein Binding"

Generating 3D Molecules for Target Protein Binding This is the official implementation of the GraphBP method proposed in the following paper. Meng Liu

DIVE Lab, Texas A&M University 74 Dec 07, 2022
Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation

Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision Training Efficiency We show the training efficiency of our DSLP model b

Chenyang Huang 36 Oct 31, 2022
Machine learning notebooks in different subjects optimized to run in google collaboratory

Notebooks Name Description Category Link Training pix2pix This notebook shows a simple pipeline for training pix2pix on a simple dataset. Most of the

Zaid Alyafeai 363 Dec 06, 2022
TrTr: Visual Tracking with Transformer

TrTr: Visual Tracking with Transformer We propose a novel tracker network based on a powerful attention mechanism called Transformer encoder-decoder a

趙 漠居(Zhao, Moju) 66 Dec 27, 2022
Code Repository for The Kaggle Book, Published by Packt Publishing

The Kaggle Book Data analysis and machine learning for competitive data science Code Repository for The Kaggle Book, Published by Packt Publishing "Lu

Packt 1.6k Jan 07, 2023
Face and other object detection using OpenCV and ML Yolo

Object-and-Face-Detection-Using-Yolo- Opencv and YOLO object and face detection is implemented. You only look once (YOLO) is a state-of-the-art, real-

Happy N. Monday 3 Feb 15, 2022
Deep Learning Pipelines for Apache Spark

Deep Learning Pipelines for Apache Spark The repo only contains HorovodRunner code for local CI and API docs. To use HorovodRunner for distributed tra

Databricks 2k Jan 08, 2023
Toolbox to analyze temporal context invariance of deep neural networks

PyTCI A toolbox that estimates the integration window of a sensory response using the "Temporal Context Invariance" paradigm (TCI). The TCI method Int

4 Oct 23, 2022
Self-training for Few-shot Transfer Across Extreme Task Differences

Self-training for Few-shot Transfer Across Extreme Task Differences (STARTUP) Introduction This repo contains the official implementation of the follo

Cheng Perng Phoo 33 Oct 31, 2022
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models

DSEE Codes for [Preprint] DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models Xuxi Chen, Tianlong Chen, Yu Cheng, Weizhu Ch

VITA 4 Dec 27, 2021
EMNLP'2021: Simple Entity-centric Questions Challenge Dense Retrievers

EntityQuestions This repository contains the EntityQuestions dataset as well as code to evaluate retrieval results from the the paper Simple Entity-ce

Princeton Natural Language Processing 119 Sep 28, 2022
a reimplementation of UnFlow in PyTorch that matches the official TensorFlow version

pytorch-unflow This is a personal reimplementation of UnFlow [1] using PyTorch. Should you be making use of this work, please cite the paper according

Simon Niklaus 134 Nov 20, 2022
A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

FedML-AI 175 Dec 01, 2022
An Exact Solver for Semi-supervised Minimum Sum-of-Squares Clustering

PC-SOS-SDP: an Exact Solver for Semi-supervised Minimum Sum-of-Squares Clustering PC-SOS-SDP is an exact algorithm based on the branch-and-bound techn

Antonio M. Sudoso 1 Nov 13, 2022
This repository contains an overview of important follow-up works based on the original Vision Transformer (ViT) by Google.

This repository contains an overview of important follow-up works based on the original Vision Transformer (ViT) by Google.

75 Dec 02, 2022
This computer program provides a reference implementation of Lagrangian Monte Carlo in metric induced by the Monge patch

This computer program provides a reference implementation of Lagrangian Monte Carlo in metric induced by the Monge patch. The code was prepared to the final version of the accepted manuscript in AIST

Marcelo Hartmann 2 May 06, 2022