The Simpsons and Machine Learning: What makes an Episode Great?

Overview

The Simpsons and Machine Learning: What makes an Episode Great?

Check out my Medium article on this!

PROBLEM:

  • The Simpsons has had a decline in quality over the years
  • A quantitative solution is required to discover what makes a quality epsiode, and how these kinds of episodes can be replicated

SOLUTION:

  • Utilized sklearn, statsmodels, matplotlib, seaborn, pandas, and numpy packages
  • Built a linear regression model to predict IMDB rating based off word count per character and location

ATTACHED FILES:

  • simpsons_characters.csv
  • simpsons_episodes.csv
  • simpsons_locations.csv
Owner
Quantitative Insight
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
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker.

SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S

Amazon Web Services 1.8k Jan 01, 2023
Machine Learning Algorithms ( Desion Tree, XG Boost, Random Forest )

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map,

Mohamadreza Rezaei 1 Jan 19, 2022
Forecasting prices using Facebook/Meta's Prophet model

CryptoForecasting using Machine and Deep learning (Part 1) CryptoForecasting using Machine Learning The main aspect of predicting the stock-related da

1 Nov 27, 2021
Scikit-learn compatible wrapper of the Random Bits Forest program written by (Wang et al., 2016)

sklearn-compatible Random Bits Forest Scikit-learn compatible wrapper of the Random Bits Forest program written by Wang et al., 2016, available as a b

Tamas Madl 8 Jul 24, 2021
PLUR is a collection of source code datasets suitable for graph-based machine learning.

PLUR (Programming-Language Understanding and Repair) is a collection of source code datasets suitable for graph-based machine learning. We provide scripts for downloading, processing, and loading the

Google Research 76 Nov 25, 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
Simple and flexible ML workflow engine.

This is a simple and flexible ML workflow engine. It helps to orchestrate events across a set of microservices and create executable flow to handle requests. Engine is designed to be configurable wit

Katana ML 295 Jan 06, 2023
slim-python is a package to learn customized scoring systems for decision-making problems.

slim-python is a package to learn customized scoring systems for decision-making problems. These are simple decision aids that let users make yes-no p

Berk Ustun 37 Nov 02, 2022
Scikit-Learn useful pre-defined Pipelines Hub

Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in

Rodrigo Arenas 1 Apr 26, 2022
Tools for diffing and merging of Jupyter notebooks.

nbdime provides tools for diffing and merging of Jupyter Notebooks.

Project Jupyter 2.3k Jan 03, 2023
Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

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

Artsem Zhyvalkouski 64 Nov 30, 2022
Machine Learning Algorithms

Machine-Learning-Algorithms In this project, the dataset was created through a survey opened on Google forms. The purpose of the form is to find the p

Göktuğ Ayar 3 Aug 10, 2022
Kalman filter library

The kalman filter framework described here is an incredibly powerful tool for any optimization problem, but particularly for visual odometry, sensor fusion localization or SLAM.

comma.ai 276 Jan 01, 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
ThunderGBM: Fast GBDTs and Random Forests on GPUs

Documentations | Installation | Parameters | Python (scikit-learn) interface What's new? ThunderGBM won 2019 Best Paper Award from IEEE Transactions o

Xtra Computing Group 648 Dec 16, 2022
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera

Intel Corporation 858 Dec 25, 2022
Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máquina.

Estatistica para Ciência de Dados e Machine Learning Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máqui

Renan Barbosa 1 Jan 10, 2022
As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Crate will be the hub of various ML projects which will be the resources for the ML enthusiasts! Open Source Program: SWOC 2021 and JWOC 2022.

Machine Learning Loot Crate 💻 🧰 🔴 Welcome contributors! As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Cra

Abhishek Sharma 89 Dec 28, 2022
Metric learning algorithms in Python

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

1.3k Dec 28, 2022