Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn

Overview

Clustering

Clustering Application in Python Using scikit-learn

This repository contains the prediction of baseball metric clusters using MLB Statcast Metrics.

ap_mlb_1_stadium

Goals

  • Using MLB Statcast Metrics, summarize and examine baseball statistics.
  • Build a k-Means Clustering model to predict clusters using exit velocity and launch angle as features.
    • Determine the optimal number of clusters using the elbow method and silhouette coefficients.
  • Build a Hierarchical (Agglomerative) Clustering model to predict clusters using exit velocity and launch angle as features.
Owner
Tom Weichle
Data Scientist w/10 years successfully finding meaningful insights in large-scale databases
Tom Weichle
Implementation of K-Nearest Neighbors Algorithm Using PySpark

KNN With Spark Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https:

Zachary Petroff 4 Dec 30, 2022
🔬 A curated list of awesome machine learning strategies & tools in financial market.

🔬 A curated list of awesome machine learning strategies & tools in financial market.

GeorgeZou 1.6k Dec 30, 2022
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar

Facebook 15.4k Jan 07, 2023
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 learn

Vowpal Wabbit 8.1k Dec 30, 2022
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

Jesùs Guillen 1 Jun 03, 2022
MiniTorch - a diy teaching library for machine learning engineers

This repo is the full student code for minitorch. It is designed as a single repo that can be completed part by part following the guide book. It uses

1.1k Jan 07, 2023
ML Optimizers from scratch using JAX

Toy implementations of some popular ML optimizers using Python/JAX

Shreyansh Singh 38 Jul 29, 2022
Pandas Machine Learning and Quant Finance Library Collection

Pandas Machine Learning and Quant Finance Library Collection

148 Dec 07, 2022
A linear regression model for house price prediction

Linear_Regression_Model A linear regression model for house price prediction. This code is using these packages, so please make sure your have install

ShawnWang 1 Nov 29, 2021
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

MLJAR 2.4k Jan 02, 2023
Python module for machine learning time series:

seglearn Seglearn is a python package for machine learning time series or sequences. It provides an integrated pipeline for segmentation, feature extr

David Burns 536 Dec 29, 2022
Gaussian Process Optimization using GPy

End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past

Sheffield Machine Learning Software 847 Dec 19, 2022
Dive into Machine Learning

Dive into Machine Learning Hi there! You might find this guide helpful if: You know Python or you're learning it 🐍 You're new to Machine Learning You

Michael Floering 11.1k Jan 03, 2023
inding a method to objectively quantify skill versus chance in games, using reinforcement learning

Skill-vs-chance-games-analysis - Finding a method to objectively quantify skill versus chance in games, using reinforcement learning

Marcus Chiam 4 Nov 19, 2022
PennyLane is a cross-platform Python library for differentiable programming of quantum computers

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural ne

PennyLaneAI 1.6k Jan 01, 2023
My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data

kNN-vs-RFR My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data In many areas, rental bikes have been launched to

1 Oct 28, 2021
Implementation of different ML Algorithms from scratch, written in Python 3.x

Implementation of different ML Algorithms from scratch, written in Python 3.x

Gautam J 393 Nov 29, 2022
This is the material used in my free Persian course: Machine Learning with Python

This is the material used in my free Persian course: Machine Learning with Python

Yara Mohamadi 4 Aug 07, 2022
We have a dataset of user performances. The project is to develop a machine learning model that will predict the salaries of baseball players.

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

Ayşe Nur Türkaslan 9 Oct 14, 2022
Xeasy-ml is a packaged machine learning framework.

xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use

9 Mar 14, 2022