We have a dataset of user performances. The project is to develop a machine learning model that will predict the salaries of baseball players.

Related tags

Machine Learning Salary-Prediction-with-Machine-Learning
Overview

Salary-Prediction-with-Machine-Learning

image

1. Business Problem

Can a machine learning project be implemented to estimate the salaries of baseball players whose salary information and career statistics for 1986 are shared?

2. Dataset Story

  • This dataset was originally taken from the StatLib library at Carnegie Mellon University.
  • The data set is part of the data used in the 1988 ASA Graphics Section Poster Session.
  • Salary data originally taken from Sports Illustrated, April 20, 1987.
  • 1986 and career statistics, Collier Books, Macmillan Publishing Company.

3. Variables

  • AtBat: Number of hits with a baseball bat during the 1986-1987 season
  • Hits: the number of hits in the 1986-1987 season
  • HmRun: Most valuable hits in the 1986-1987 season
  • Runs: The points he earned for his team in the 1986-1987 season
  • RBI: The number of players a batter had jogged when he hit
  • Walks: Number of mistakes made by the opposing player
  • Years: Player's playing time in major league (years)
  • CAtBat: The number of times the player hits the ball during his career
  • CHits: The number of hits the player has made throughout his career
  • CHmRun: The player's most valuable number during his career
  • CRuns: The number of points the player has earned for his team during his career
  • CRBI: The number of players the player has made during his career
  • CWalks: The number of mistakes the player has made to the opposing player during his career
  • League: A factor with levels A and N, showing the league in which the player played until the end of the season
  • Division: a factor with levels E and W, indicating the position played by the player at the end of 1986
  • PutOuts: Helping your teammate in-game
  • Assits: The number of assists the player made in the 1986-1987 season
  • Errors: the number of errors of the player in the 1986-1987 season
  • Salary: The salary of the player in the 1986-1987 season (over thousand)
  • NewLeague: a factor with levels A and N indicating the league of the player at the beginning of the 1987 season

TASK

Salary using data preprocessing and feature engineering techniques develop a forecasting model

You might also like...
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Epistasis Lab at UPenn 8.9k Jan 9, 2023
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Augusto Almeida 84 Nov 25, 2022
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

Vowpal Wabbit 8.1k Dec 30, 2022
CD) in machine learning projectsImplementing continuous integration & delivery (CI/CD) in machine learning projects

CML with cloud compute This repository contains a sample project using CML with Terraform (via the cml-runner function) to launch an AWS EC2 instance

Iterative 19 Oct 3, 2022
learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your personal portfolio
learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your personal portfolio

learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your personal portfolio

BDFD 6 Nov 5, 2022
A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!

Stox A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural Network and the LSTM algorithm to predict

Stox 31 Dec 16, 2022
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Microsoft 241 Dec 26, 2022
This repository contains the code to predict house price using Linear Regression Method
This repository contains the code to predict house price using Linear Regression Method

House-Price-Prediction-Using-Linear-Regression The dataset I used for this personal project is from Kaggle uploaded by aariyan panchal. Link of Datase

null 0 Jan 28, 2022
Predict profitability of trades based on indicator buy / sell signals

Predict profitability of trades based on indicator buy / sell signals Trade profitability analysis for trades based on various indicators signals: MAC

Tomasz Porzycki 1 Dec 15, 2021
Owner
Ayşe Nur Türkaslan
I continue my studies in the field of Data Science and Artificial Intelligence. I want to turn my efforts into a contribution using Github
Ayşe Nur Türkaslan
GitHub
Predicting job salaries from ads - a Kaggle competition

Predicting job salaries from ads - a Kaggle competition

Zygmunt Zając 57 Oct 23, 2020
Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn

Clustering Clustering Application in Python Using scikit-learn This repository contains the prediction of baseball metric clusters using MLB Statcast

Tom Weichle 2 Apr 18, 2022
Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

null 15 Sep 9, 2022
machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service

This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made this project as a requirement for an internship at Indian Servers. We are now making it open to contribution.

Krishna Priyatham Potluri 73 Dec 1, 2022
pure-predict: Machine learning prediction in pure Python

pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks like scikit-learn and fasttext. It implements the predict methods of these frameworks in pure Python.

Ibotta 84 Dec 29, 2022
This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you ask it.

Crypto-Currency-Predictor This machine-learning algorithm takes in data from the last 60 days and tries to predict tomorrow's price of any crypto you

Hazim Arafa 6 Dec 4, 2022
Uses WiFi signals :signal_strength: and machine learning to predict where you are

Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.

Pascal van Kooten 5k Jan 9, 2023
A model to predict steering torque fully end-to-end

torque_model The torque model is a spiritual successor to op-smart-torque, which was a project to train a neural network to control a car's steering f

Shane Smiskol 4 Jun 3, 2022
Ml based project which uses regression technique to predict the price.

Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with

Garvit Verma 1 Jul 9, 2022
CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning applications.

SmartSim Example Zoo This repository contains CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning appl

Cray Labs 14 Mar 30, 2022