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
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 09, 2022
End to End toy example of MLOps

churn_model MLOps Toy Example End to End You might find below links useful Connect VSCode to Git MLFlow Port Heroku App Project Organization ├── LICEN

Ashish Tele 6 Feb 06, 2022
Course files for "Ocean/Atmosphere Time Series Analysis"

time-series This package contains all necessary files for the course Ocean/Atmosphere Time Series Analysis, an introduction to data and time series an

Jonathan Lilly 107 Nov 29, 2022
Test symmetries with sklearn decision tree models

Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro

Rupert Tombs 2 Jul 19, 2022
XGBoost + Optuna

AutoXGB XGBoost + Optuna: no brainer auto train xgboost directly from CSV files auto tune xgboost using optuna auto serve best xgboot model using fast

abhishek thakur 517 Dec 31, 2022
LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms

LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query

5 Aug 06, 2022
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

alkaline-ml 1.3k Jan 06, 2023
Automated Machine Learning with scikit-learn

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

AutoML-Freiburg-Hannover 6.7k Jan 07, 2023
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
Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning

Azure Cloud Advocates at Microsoft are pleased to offer a 12-week, 24-lesson curriculum all about Machine Learning

Microsoft 43.4k Jan 04, 2023
This is an auto-ML tool specialized in detecting of outliers

Auto-ML tool specialized in detecting of outliers Description This tool will allows you, with a Dash visualization, to compare 10 models of machine le

1 Nov 03, 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
ThunderSVM: A Fast SVM Library on GPUs and CPUs

What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss

Xtra Computing Group 1.4k Dec 22, 2022
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 03, 2022
A handy tool for common machine learning models' hyper-parameter tuning.

Common machine learning models' hyperparameter tuning This repo is for a collection of hyper-parameter tuning for "common" machine learning models, in

Kevin Hu 2 Jan 27, 2022
A collection of Machine Learning Models To Web Api which are built on open source technologies/frameworks like Django, Flask.

Author Ibrahim Koné From-Machine-Learning-Models-To-WebAPI A collection of Machine Learning Models To Web Api which are built on open source technolog

Ibrahim Koné 2 May 24, 2022
TIANCHI Purchase Redemption Forecast Challenge

TIANCHI Purchase Redemption Forecast Challenge

Haorui HE 4 Aug 26, 2022
customer churn prediction prevention in telecom industry using machine learning and survival analysis

Telco Customer Churn Prediction - Plotly Dash Application Description This dash application allows you to predict telco customer churn using machine l

Benaissa Mohamed Fayçal 3 Nov 20, 2021
This is a Machine Learning model which predicts the presence of Diabetes in Patients

Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s

Edem Gold 4 Mar 16, 2022
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

Astitva Veer Garg 1 Jan 11, 2022