Gems & Holiday Package Prediction

Overview

Predictive_Modelling

Gems & Holiday Package Prediction

This project is based on 2 cases studies : Gems Price Prediction and Holiday Package prediction. In the first case study, concepts of linear regression are tested and it is expected from the learner to predict the price of gems based on multiple variables to help company maximize profits. In the second case, concepts of logistic regression and linear discriminant analysis are tested. One has to predict if the customer will purchase the holiday package to target the relevant customer base.

Skills and Tools

Linear Regression, Logistic Regression, Linear discriminant Analysis

Owner
Avnika Mehta
Avnika Mehta
Visyerres sgdf woob - Modules Woob pour l'intranet et autres sites Scouts et Guides de France

Vis'Yerres SGDF - Modules Woob Vous avez le sentiment que l'intranet des Scouts

Thomas Touhey (pas un pseudonyme) 3 Dec 24, 2022
AI drive app that can help user become beautiful.

爱美丽 Beauty 简体中文 Features Beauty is an AI drive app that can help user become beautiful. it contain those functions: face score cheek face beauty repor

Starved Midnight 1 Jan 30, 2022
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks

Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi

Giacomo Arcieri 1 Mar 21, 2022
The "breathing k-means" algorithm with datasets and example notebooks

The Breathing K-Means Algorithm (with examples) The Breathing K-Means is an approximation algorithm for the k-means problem that (on average) is bette

Bernd Fritzke 75 Nov 17, 2022
Pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion"

MOSNet pytorch implementation of "MOSNet: Deep Learning based Objective Assessment for Voice Conversion" https://arxiv.org/abs/1904.08352 Dependency L

9 Nov 18, 2022
What can linearized neural networks actually say about generalization?

What can linearized neural networks actually say about generalization? This is the source code to reproduce the experiments of the NeurIPS 2021 paper

gortizji 11 Dec 09, 2022
A paper using optimal transport to solve the graph matching problem.

GOAT A paper using optimal transport to solve the graph matching problem. https://arxiv.org/abs/2111.05366 Repo structure .github: Files specifying ho

neurodata 8 Jan 04, 2023
Official Pytorch implementation of "Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes", CVPR 2022

Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenes / 3DCrowdNet News 💪 3DCrowdNet achieves the state-of-the-art accuracy on 3D

Hongsuk Choi 113 Dec 21, 2022
Vision Deep-Learning using Tensorflow, Keras.

Welcome! I am a computer vision deep learning developer working in Korea. This is my blog, and you can see everything I've studied here. https://www.n

kimminjun 6 Dec 14, 2022
Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight)

[NeurIPS 2021 Spotlight] HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning [Paper] This is Official PyTorch implementatio

42 Nov 01, 2022
SEJE Pytorch implementation

SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. Contents Inst

0 Oct 21, 2021
A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano

yolov5-fire-smoke-detect-python A python implementation of Yolov5 to detect fire or smoke in the wild in Jetson Xavier nx and Jetson nano You can see

20 Dec 15, 2022
Replication of Pix2Seq with Pretrained Model

Pretrained-Pix2Seq We provide the pre-trained model of Pix2Seq. This version contains new data augmentation. The model is trained for 300 epochs and c

peng gao 51 Nov 22, 2022
Diagnostic tests for linguistic capacities in language models

LM diagnostics This repository contains the diagnostic datasets and experimental code for What BERT is not: Lessons from a new suite of psycholinguist

61 Jan 02, 2023
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come

IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, and soon Pytorch Image Models. It or

airctic 789 Dec 29, 2022
PyTorch implementation of the Value Iteration Networks (VIN) (NIPS '16 best paper)

Value Iteration Networks in PyTorch Tamar, A., Wu, Y., Thomas, G., Levine, S., and Abbeel, P. Value Iteration Networks. Neural Information Processing

LEI TAI 75 Nov 24, 2022
source code for 'Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge' by A. Shah, K. Shanmugam, K. Ahuja

Source code for "Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge" Reference: Abhin Shah, Karthikeyan Shanmugam, Kartik Ahu

Abhin Shah 1 Jun 03, 2022
Tool for live presentations using manim

manim-presentation Tool for live presentations using manim Install pip install manim-presentation opencv-python Usage Use the class Slide as your sce

Federico Galatolo 146 Jan 06, 2023
A keras-based real-time model for medical image segmentation (CFPNet-M)

CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation This repository contains the implementat

268 Nov 27, 2022
Keras Implementation of The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation by (Simon Jégou, Michal Drozdzal, David Vazquez, Adriana Romero, Yoshua Bengio)

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation: Work In Progress, Results can't be replicated yet with the m

Yad Konrad 196 Aug 30, 2022