Python Kaggle-advertised-salaries Resources

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

Kaggle-Happywhale Happywhale - Whale and Dolphin Identification Silver 🥈 Solution (26/1588) 竞赛方案思路 图像数据预处理-标志性特征图片裁剪：首先根据开源的标注数据训练YOLOv5x6目标检测模型，将训练集

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

30-Days-of-ML-Kaggle 🔥 About the Hands On Program 💻 Machine learning beginner → Kaggle competitor in 30 days. Non-coders welcome The program starts

Feedback Prize - Evaluating Student Writing This is the solution for 2nd rank in Kaggle competition: Feedback Prize - Evaluating Student Writing. The

handm_data_visualize_app Data visualization app by streamlit for H&M competition in kaggle. competition page: https://www.kaggle.com/competitions/h-an

Kaggle Competition: Forest Cover Type Prediction In this project we predict the forest cover type (the predominant kind of tree cover) using the carto

Kaggle Feedback Prize - Evaluating Student Writing 15th solution First of all, I would like to thank the excellent notebooks and discussions from http

AutoLGBM LightGBM + Optuna: no brainer auto train lightgbm directly from CSV files auto tune lightgbm using optuna auto serve best lightgbm model usin

hh_ru_research Проект реализован в учебных целях анализа рынка труда, в особенности по hh.ru Input data В качестве входных данных используются сериали

PruebaEnel Prueba Kaggle-Springleaf-master Prueba Kaggle-Springleaf Kaggle competition: Springleaf Marketing Response Competencia de Kaggle: Marketing

🔥 Olympics Data Analysis 🔥 In Data Science field, there is a big topic before creating a model for future prediction is Data Analysis. We can find o

Credit Card Fraud Detection, used the credit card fraud dataset from Kaggle

Kaggleship: Kaggle Notebooks This repository contains my Kaggle notebooks. They are generally about data science, machine learning, and deep learning.

Predicting Auction Sale Price using the kaggle bulldozer auction sales data: Modeling with Ensembles vs Neural Network The performances of tree ensemb

Kaggle DSTL Satellite Imagery Feature Detection

ARM This jupyter notebook project was completed by me and my friend using the dataset from Kaggle. The world Happiness 2017, which ranks 155 countries

Home Credit Default Risk: Open Solution This is an open solution to the Home Credit Default Risk challenge 🏡 . More competitions 🎇 Check collection

Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t

Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple

Predicting job salaries from ads - a Kaggle competition

Winning solution for the Galaxy Challenge on Kaggle

The aim of the mini project is predict whether or not a passenger survived based on attributes such as their age, sex, passenger class, where they embarked and more.

Gender discrimination based on handwriting See http://fastml.com/gender-discrimination/ for description. prep_data.py - a first step chunk_by_authors.

Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.

TensorFlow Tutorial - used by Nvidia Learn TensorFlow from scratch by examples and visualizations with interactive jupyter notebooks. Learn to compete

2019-indian-election-eda Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle. This project is a part of the Cou

Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products.

IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the one with a higher score and less overfitting.

Sartorius - Cell Instance Segmentation https://www.kaggle.com/c/sartorius-cell-instance-segmentation Environment setup Build docker image bash .dev_sc

G-Research-Crypto-Competition Project for passing the ML exam. Dataset took from

Kaggle-titanic This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this reposito

Kaggle-2019-Data-Science-Bowl-Solution - Here i present my solution to kaggle 2019 data science bowl and how i improved it to win a silver medal in that competition.

Global-Wheat-Detection An efficient PyTorch library for Global Wheat Detection using YOLOv5. The project is based on this Kaggle competition Global Wh

Lux AI 2021 python game engine and gym This is a replica of the Lux AI 2021 game ported directly over to python. It also sets up a classic Reinforceme

Kaggle-Comp.-Data-Mining Kaggle Competition using 15 numerical predictors to predict a continuous outcome as part of a final project for a stats data

Zillow-Houses This repository contains full machine learning pipeline of the Zillow Houses competition on Kaggle platform. Pipeline is consists of 10

-ML-Kaggle-Titanic-Problem-using-LogisticRegrission here you will find the solution for the titanic problem on kaggle with comments and step by step c

kaggle_titanic_deploy Project to deploy a machine learning model based on Titanic dataset from Kaggle In this project we used the Titanic dataset from

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

This is the code used in the paper "Entity Embeddings of Categorical Variables". If you want to get the original version of the code used for the Kagg

Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation By Vladimir Iglovikov and Alexey Shvets Introduction TernausNet is

Ultrasound Nerve Segmentation Challenge using Torchnet This repository acts as a starting point for someone who wants to start with the kaggle ultraso

Ultrasound nerve segmentation using Keras (1.0.7) Kaggle Ultrasound Nerve Segmentation competition [Keras] #Install (Ubuntu {14,16}, GPU) cuDNN requir

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne

The 2nd place solution of 2021 google landmark retrieval on kaggle.

END TO END MACHINE LEARNING PROJECT ON HITTERS DATASET Can a machine learning project be implemented to estimate the salaries of baseball players whos

PyTorch Image Classification Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to

Kaggle: Cell Instance Segmentation The goal of this challenge is to detect cells in microscope images. with simple view on how many cels have been ann

Google Landmark Recogntion and Retrieval 2021 Solutions In this repository you can find solution and code for Google Landmark Recognition 2021 and Goo

Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka

Salary-Prediction-with-Machine-Learning 1. Business Problem Can a machine learning project be implemented to estimate the salaries of baseball players

Google_Landmark_Retrieval_2021_2nd_Place_Solution The 2nd place solution of 2021 google landmark retrieval on kaggle. Environment We use cuda 11.1/pyt

Kaggle G2Net Gravitational Wave Detection : 2nd place solution

CNN (InceptionV1) + STFT based Whale Detection Algorithm So, this repository is my PyTorch solution for the Kaggle whale-detection challenge. The obje

Example of network fine-tuning in pytorch for the kaggle competition Dogs vs. Cats Redux: Kernels Edition Currently

D2L.ai: Interactive Deep Learning Book with Multi-Framework Code, Math, and Discussions Book website | STAT 157 Course at UC Berkeley | Latest version

Lux AI Working Title Bot Please refer to the Kaggle notebook for the comment section. The comment section contains my explanation on my code structure

Riiid Answer Correctness Prediction Introduction This repository is the code that placed 78th in Riiid Answer Correctness Prediction competition. Requ

TF Watcher TF Watcher is a simple to use Python package and web app which allows you to monitor 👀 your Machine Learning training or testing process o

Under refactoring 10th place solution for Google Smartphone Decimeter Challenge at kaggle. Google Smartphone Decimeter Challenge Global Navigation Sat

Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Deep Learning Winter School, November 2107. Tel Aviv Deep Learning Bootcamp : http://deep-ml.com. About Tel-Aviv Deep Learning Bootcamp is an intensiv

Amazon Forest Computer Vision Satellite Image tagging code using PyTorch / Keras Here is a sample of images we had to work with Source: https://www.ka

UNet for segmenting salt deposits from seismic images with PyTorch. General We, tugstugi and xuyuan, have participated in the Kaggle competition TGS S

XGBoost-Ray is a distributed backend for XGBoost, built on top of distributed computing framework Ray.

1st place solution at Kaggle Hotel-ID My 1st place solution at Kaggle Hotel-ID to Combat Human Trafficking 2021. https://www.kaggle.com/c/hotel-id-202

Part of the 9th place solution for the Bristol-Myers Squibb – Molecular Translation challenge translating images containing chemical structures into I

kaggle-hpa-2021-7th-place-solution Code for 7th place solution of Human Protein Atlas - Single Cell Classification on Kaggle. A description of the met

This repository contains the code to generate the winning solution of the Kaggle competition on indoor location and navigation organized by Microsoft

TorchFlare TorchFlare is a simple, beginner-friendly and an easy-to-use PyTorch Framework train your models without much effort. It provides an almost

🏅 Collection of Kaggle Solutions and Ideas 🏅

Pytorch-toolbelt A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming: What

RANZCR-CLiP 7th Place Solution This repository is WIP. (18 Mar 2021) Installation git clone https://github.com/analokmaus/kaggle-ranzcr-clip-public.gi

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle

Santa 2020 - The Candy Cane Contest My solution in this Kaggle competition "Santa 2020 - The Candy Cane Contest", 9th place. Basic Strategy In this co

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

The 3rd place solution for competition "Lyft Motion Prediction for Autonomous Vehicles" at Kaggle Team behind this solution: Artsiom Sanakoyeu [Homepa

Lyft Motion Prediction for Autonomous Vehicles Code for the 4th place solution of Lyft Motion Prediction for Autonomous Vehicles on Kaggle. Discussion

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r