9th place solution in "Santa 2020 - The Candy Cane Contest"
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Updated
Feb 23, 2021 - Python
9th place solution in "Santa 2020 - The Candy Cane Contest"
Crypto & Stock* price prediction with regression models.
This repository will work around solving the problem of food demand forecasting using machine learning.
Amazon SageMaker Examples
This repository contains code and resources for an end-to-end regression project on retail sales prediction. The goal of this project is to develop a regression model that can accurately predict retail sales based on various features.
Predicting the Residential Energy Usage across 113.6 million U.S. households using Machine Learning Algorithms (Regression and Ensemble)
In this section, we will use machine learning algorithms to perform time series analysis.
Notes, tutorials, code snippets and templates focused on LightGBM for Machine Learning
Automobile dataset for used Car Price Analysis to predict the price of a vehicle with their features and performance factor to provide the exact value of a vehicle for buyer seller satisfaction using exploratory data analysis and machine learning models.
A Machine Learning Case Study based on helping the company target customers by predicting the customer loyalty score based on the transactions data.
Analysis of time series data from IoT devices
Silver medal solution for the "M5 Forecasting - Accuracy" Kaggle competition
This machine learning model was developed for "House Prices - Advanced Regression Techniques" competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.
This code demonstrates the use of machine learning to model the multimodal nature of a single cell. Using machine learning to predict RNA from DNA, that is, using chromatin accessibility data to predict the RNA gene expression and to predict surface protein from RNA, that is, using RNA sequence data to predict surface protein levels in a cell
This repository contains my solution for the Kaggle competition Automated Essay Scoring 2.0. The goal of this project is to develop an automated system capable of scoring essays based on their content and quality using machine learning techniques.
This project develops a machine learning model to predict the salaries of baseball players based on their past performance.
Projeto de previsões de pontos de chegada em corridas de táxi na cidade do Porto, Portugal.
Using LightGBM and Other Models for Car Prices' Prediction – Study Project for Yandex Practicum
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