Gems & Holiday Package Prediction

Last update: Jan 27, 2022

Related tags

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

GitHub Repository

Multiview 3D object detection on MultiviewC dataset through moft3d.

Voxelized 3D Feature Aggregation for Multiview Detection [arXiv] Multiview 3D object detection on MultiviewC dataset through VFA. Introduction We prop

20 Dec 21, 2022

This program uses trial auth token of Azure Cognitive Services to do speech synthesis for you.

🗣️ aspeak A simple text-to-speech client using azure TTS API(trial). 😆 TL;DR: This program uses trial auth token of Azure Cognitive Services to do s

359 Jan 05, 2023

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation

1 Jan 22, 2022

Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure.

Event Queue Dialect Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure. Motivation The m

23 Dec 08, 2022

SeqAttack: a framework for adversarial attacks on token classification models

A framework for adversarial attacks against token classification models

23 Nov 25, 2022

Federated_learning codes used for the the paper "Evaluation of Federated Learning Aggregation Algorithms" and "A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison"

Federated Distance (FedDist) This is the code accompanying the Percom2021 paper "A Federated Learning Aggregation Algorithm for Pervasive Computing: E

8 Jan 03, 2023

Gems & Holiday Package Prediction

Related tags

Overview

Predictive_Modelling

Owner

Avnika Mehta

Multiview 3D object detection on MultiviewC dataset through moft3d.

This program uses trial auth token of Azure Cognitive Services to do speech synthesis for you.

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work

Event queue (Equeue) dialect is an MLIR Dialect that models concurrent devices in terms of control and structure.

SeqAttack: a framework for adversarial attacks on token classification models

Federated_learning codes used for the the paper "Evaluation of Federated Learning Aggregation Algorithms" and "A Federated Learning Aggregation Algorithm for Pervasive Computing: Evaluation and Comparison"

Pixray is an image generation system

The 3rd place solution for competition

Aspect-Sentiment-Multiple-Opinion Triplet Extraction (NLPCC 2021)

Some useful blender add-ons for SMPL skeleton's poses and global translation.

Training RNNs as Fast as CNNs

VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition

A universal framework for learning timestamp-level representations of time series

PyTorch implementation of residual gated graph ConvNets, ICLR’18

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

A PyTorch implementation of Sharpness-Aware Minimization for Efficiently Improving Generalization

Human-Pose-and-Motion History

Manifold-Mixup implementation for fastai V2

N-gram models- Unsmoothed, Laplace, Deleted Interpolation

Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)