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

Related tags

Machine Learningthe-simpsons-and-machine-learning
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
GitHub Repository
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.

Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp

AutoViz and Auto_ViML 519 Jan 03, 2023
Climin is a Python package for optimization, heavily biased to machine learning scenarios

climin climin is a Python package for optimization, heavily biased to machine learning scenarios distributed under the BSD 3-clause license. It works

Biomimetic Robotics and Machine Learning at Technische Universität München 177 Sep 02, 2022
Client - 🔥 A tool for visualizing and tracking your machine learning experiments

Weights and Biases Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to produ

Weights & Biases 5.2k Jan 03, 2023
Send rockets to Mars with artificial intelligence(Genetic algorithm) in python.

Send Rockets To Mars With AI Send rockets to Mars with artificial intelligence(Genetic algorithm) in python. Tools Python 3 EasyDraw How to Play Insta

Mohammad Dori 3 Jul 15, 2022
This project has Classification and Clustering done Via kNN and K-Means respectfully

This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. T

Mohammad Ali Mustafa 0 Jan 20, 2022
Library for machine learning stacking generalization.

stacked_generalization Implemented machine learning *stacking technic[1]* as handy library in Python. Feature weighted linear stacking is also availab

114 Jul 19, 2022
Adversarial Framework for (non-) Parametric Image Stylisation Mosaics

Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag

Zalando Research 120 Dec 24, 2022
Practical Time-Series Analysis, published by Packt

Practical Time-Series Analysis This is the code repository for Practical Time-Series Analysis, published by Packt. It contains all the supporting proj

Packt 325 Dec 23, 2022
Traingenerator 🧙 A web app to generate template code for machine learning ✨

Traingenerator 🧙 A web app to generate template code for machine learning ✨ 🎉 Traingenerator is now live! 🎉

Johannes Rieke 1.2k Jan 07, 2023
Time series forecasting with PyTorch

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

Jan Beitner 2.5k Jan 02, 2023
A Lucid Framework for Transparent and Interpretable Machine Learning Models.

Currently a Beta-Version lucidmode is an open-source, low-code and lightweight Python framework for transparent and interpretable machine learning mod

lucidmode 15 Aug 12, 2022
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft 366 Jan 03, 2023
PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors.

PyNNDescent PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors. It provides a python implementation of Nearest Neighbo

Leland McInnes 699 Jan 09, 2023
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
Real-time stream processing for python

Streamz Streamz helps you build pipelines to manage continuous streams of data. It is simple to use in simple cases, but also supports complex pipelin

Python Streamz 1.1k Dec 28, 2022
Upgini : data search library for your machine learning pipelines

Automated data search library for your machine learning pipelines → find & deliver relevant external data & features to boost ML accuracy :chart_with_upwards_trend:

Upgini 175 Jan 08, 2023
💀mummify: a version control tool for machine learning

mummify is a version control tool for machine learning. It's simple, fast, and designed for model prototyping.

Max Humber 43 Jul 09, 2022
Simplify stop motion animation with machine learning.

Simplify stop motion animation with machine learning.

Nick Bild 25 Sep 15, 2022
Covid-polygraph - a set of Machine Learning-driven fact-checking tools

Covid-polygraph, a set of Machine Learning-driven fact-checking tools that aim to address the issue of misleading information related to COVID-19.

1 Apr 22, 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