PenguinSpeciesPredictionML - Basic model to predict Penguin species based on beak size and sex.

Overview

Penguin Species Prediction (ML) 🐧 👨🏽‍💻

What? 💻

This project is a basic model using sklearn methods to predict Penguin species based on beak size and sex. It is inspired by Moshfegh Hamedani of Programming with Mosh who did the same project, but to predict preferred music genre from sex and age. The project includes a jupyter notebook file with all of the code to load and process the data as well as train, analyze, and test the model. The file also creates a .dot file which generates an included visualisation of the model's decision tree. The repository includes this .dot file and corresponding image as well as the .joblib file (containing the model) and of course, the data itself.

Why? 🤔

This was my first real taste of an independent machine learning project - I was involved in a past project involving ML to predict chat-bot input data about various categories, but I was not as hands on as I'd have liked. I really just wanted to get a better sense of ML and work a bit more with sklearn using data that I was interested in. I found this dataset by searching through kaggle (and Google) for 'good machine learning data' and ended up selecting it because I haven't been able to work with animal/zoology data yet.

Owner
Tucker Paron
University of Vermont | B.S. Data Science '22 | M.S. Complex Systems '23
Tucker Paron
Place holder for HOPE: a human-centric and task-oriented MT evaluation framework using professional post-editing

HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation Place holder for dat

Lifeng Han 1 Apr 25, 2022
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model

Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model About This repository contains the code to replicate the syn

Haruka Kiyohara 12 Dec 07, 2022
Multi agent DDPG algorithm written in Python + Pytorch

Multi agent DDPG algorithm written in Python + Pytorch. It also includes a Jupyter notebook, Tennis.ipynb, as a showcase.

Rogier Wachters 2 Feb 26, 2022
Language Models Can See: Plugging Visual Controls in Text Generation

Language Models Can See: Plugging Visual Controls in Text Generation Authors: Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lin

Yixuan Su 195 Dec 22, 2022
A PoC Corporation Relationship Knowledge Graph System on top of Nebula Graph.

Corp-Rel is a PoC of Corpartion Relationship Knowledge Graph System. It's built on top of the Open Source Graph Database: Nebula Graph with a dataset

Wey Gu 20 Dec 11, 2022
Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, Amr Ahmed. KDD 2019.

gHHC Code for: Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space. Nicholas Monath, Manzil Zaheer, D

Nicholas Monath 35 Nov 16, 2022
Winning solution of the Indoor Location & Navigation Kaggle competition

This repository contains the code to generate the winning solution of the Kaggle competition on indoor location and navigation organized by Microsoft

Tom Van de Wiele 62 Dec 28, 2022
Learning Synthetic Environments and Reward Networks for Reinforcement Learning

Learning Synthetic Environments and Reward Networks for Reinforcement Learning We explore meta-learning agent-agnostic neural Synthetic Environments (

AutoML-Freiburg-Hannover 16 Sep 02, 2022
A knowledge base construction engine for richly formatted data

Fonduer is a Python package and framework for building knowledge base construction (KBC) applications from richly formatted data. Note that Fonduer is

HazyResearch 386 Dec 05, 2022
Conceptual 12M is a dataset containing (image-URL, caption) pairs collected for vision-and-language pre-training.

Conceptual 12M We introduce the Conceptual 12M (CC12M), a dataset with ~12 million image-text pairs meant to be used for vision-and-language pre-train

Google Research Datasets 226 Dec 07, 2022
Implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork.

YOLOv4-large This is the implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork. YOLOv4-CSP YOLOv4-tiny YOLOv4-

Kin-Yiu, Wong 2k Jan 02, 2023
GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)

GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network

Data Analytics and Machine Learning Group 124 Dec 30, 2022
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

Class-balanced-loss-pytorch Pytorch implementation of the paper Class-Balanced Loss Based on Effective Number of Samples presented at CVPR'19. Yin Cui

Vandit Jain 697 Dec 29, 2022
Dynamic Capacity Networks using Tensorflow

Dynamic Capacity Networks using Tensorflow Dynamic Capacity Networks (DCN; http://arxiv.org/abs/1511.07838) implementation using Tensorflow. DCN reduc

Taeksoo Kim 8 Feb 23, 2021
BrainGNN - A deep learning model for data-driven discovery of functional connectivity

A deep learning model for data-driven discovery of functional connectivity https://doi.org/10.3390/a14030075 Usman Mahmood, Zengin Fu, Vince D. Calhou

Usman Mahmood 3 Aug 28, 2022
DL course co-developed by YSDA, HSE and Skoltech

Deep learning course This repo supplements Deep Learning course taught at YSDA and HSE @fall'21. For previous iteration visit the spring21 branch. Lec

Yandex School of Data Analysis 1.3k Dec 30, 2022
Multiview 3D object detection on MultiviewC dataset through moft3d.

Voxelized 3D Feature Aggregation for Multiview Detection [arXiv] Multiview 3D object detection on MultiviewC dataset through VFA. Introduction We prop

Jiahao Ma 20 Dec 21, 2022
Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras

Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals

Federico Lopez 2 Jan 14, 2022
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator

DRL-robot-navigation Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gra

87 Jan 07, 2023
Applying PVT to Semantic Segmentation

Applying PVT to Semantic Segmentation Here, we take MMSegmentation v0.13.0 as an example, applying PVTv2 to SemanticFPN. For details see Pyramid Visio

35 Nov 30, 2022