learning-curve | Topic | Ecosyste.ms: Repos

Topic: "learning-curve"

faridcher/ml-course

Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language

Language: R - Size: 36.5 MB - Last synced at: 9 months ago - Pushed at: 11 months ago - Stars: 168 - Forks: 150

utkuufuk/coursera-machine-learning 📦

My lecture notes and assignment solutions for the Coursera machine learning class taught by Andrew Ng.

Language: Matlab - Size: 63.6 MB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 33 - Forks: 19

mohadeseh-ghafoori/Coursera-Machine-Learning-Specialization

Language: Jupyter Notebook - Size: 45.1 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 7 - Forks: 6

vaibhavnaagar/machineLearning-exercises

Machine Learning Exercises from Online Course (Coursera)

Language: Matlab - Size: 74 MB - Last synced at: about 2 years ago - Pushed at: over 8 years ago - Stars: 7 - Forks: 1

nickcafferry/Machine-Learning-in-Molecular-Sciences

2017 Summer School on the Machine Learning in the Molecular Sciences. This project aims to help you understand some basic machine learning models including neural network optimization plan, random forest, parameter learning, incremental learning paradigm, clustering and decision tree, etc. based on kernel regression and dimensionality reduction, feature selection and clustering technology.

Language: Jupyter Notebook - Size: 109 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 5 - Forks: 1

spChalk/Vaccine-Sentiment-Classifier

:syringe: Vaccine Sentiment Classifier is a deep learning classifier trained on real world twitter data, that distinguishes 3 types of tweets: Neutral, Anti-vax & Pro-vax.

Language: Jupyter Notebook - Size: 10 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0

sushant1827/Predicting-Boston-Housing-Prices

Machine Learning Nano-degree Project : To assist a real estate agent and his/her client with finding the best selling price for their home

Language: Jupyter Notebook - Size: 160 KB - Last synced at: 19 days ago - Pushed at: over 5 years ago - Stars: 3 - Forks: 5

deeptechlabs/tuner.algo.extrapol

Tuner Implementation of Extrapolating Learning Curves

Language: Python - Size: 67.4 KB - Last synced at: 11 months ago - Pushed at: almost 7 years ago - Stars: 3 - Forks: 1

kk289/ML-Regularized_Linear_Regression-Bias_Variance-MATLAB

Here, we implement regularized linear regression to predict the amount of water flowing out of a dam using the change of water level in a reservoir. In the next half, we go through some diagnostics of debugging learning algorithms and examine the effects of bias v.s. variance.

Language: MATLAB - Size: 2.32 MB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 0

AsajuHuishi/examples_sklearn.learning_curve

Some applications on functions of sklearn.learning_curve

Language: Python - Size: 80.1 KB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 2 - Forks: 0

ttungl/Machine-Learning

Machine learning techniques, such as Linear Regression, Logistic Regression, Neural Networks (feedforward propagation, backpropagation algorithms), Diagnosing Bias/Variance, Evaluating a Hypothesis, Learning Curves, Error Analysis, Support Vector Machines, K-Means Clustering, PCA, Anomaly Detection System, and Recommender System.

Language: Matlab - Size: 73.8 MB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 2 - Forks: 4

Jamster3000/BlazorWASMGithub

A learning-curve to learn if and how to get a Blazor WASM running on github pages

Language: CSS - Size: 9.8 MB - Last synced at: about 1 month ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0

SajjadAli54/cataract-classification

Cataract classification

Language: Jupyter Notebook - Size: 10.4 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

Jayveersinh-Raj/ML_IU_Study_Material

This is a collection of markdown, notebooks and/or other types of files. The images used inside are mostly from Andrew Ng and his courses. This is useful for topic vise study, and preparations. It might contain some images from the ML course offered at Innopolis University. A student from IU can use this to get good score in that course, it covers all the topics covered (as of 2022) in that course, and more.

Language: Jupyter Notebook - Size: 3.38 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

stephaniaslis/Salary

Previsão do salário (acima ou abaixo de 50K) utilizando decision tree classifier, otimização por random search, cross validation, validation curve, learning curve.

Language: Jupyter Notebook - Size: 977 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

sflender/deep-learning-test

Exploring deep learning on Cooley

Language: Jupyter Notebook - Size: 318 KB - Last synced at: about 2 months ago - Pushed at: over 7 years ago - Stars: 1 - Forks: 0

sehresh92/Data-Mining-Project

Hi, I am Sehresh Mehboob and Welcome to my Data Mining Project on SuperMarket dataset

Size: 808 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

harmanveer-2546/NBA-HOMECOURT-ADVANTAGE-DATA-ANALYSIS

In this repo we're diving into NBA game data to explore the phenomenon of home court advantage.

Language: Jupyter Notebook - Size: 1.44 MB - Last synced at: 20 days ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

georgiy-vasilevskiy/pet_project_cd_covers

Личный проект в области Computer Vision

Language: HTML - Size: 10.1 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

emrecanduran/Bike-Rental-Regression-Models

This repository contains code for a bike rental prediction models including Random Forest, XGBoost, GradientBoosting, and Lasso Regression.

Language: Jupyter Notebook - Size: 14.9 MB - Last synced at: 10 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

emrecanduran/Marketing-Campaign-Response-Prediction

Develop a model to predict which retail customers will respond to a marketing campaign. Logistic Regression shows the best performance.

Language: Jupyter Notebook - Size: 4.65 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0

emrecanduran/Marketing-Campaign-Classification

In this repository, two tree-based models from different families-bagging(RF) and boosting(XGB)- are implemented using the CRISP-DM process to predict responses for a marketing campaign, incorporating Borderline-SMOTE to effectively tackle the imbalance in the dataset.

Language: Jupyter Notebook - Size: 3.64 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0

CZheee/Deep-Learning

Deep Learning using apple quality dataset

Language: Python - Size: 2.93 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

farrellwahyudi/Predicting-Ad-Clicks-Classification-by-Using-Machine-Learning

In this project I used ML modeling and data analysis to predict ad clicks and significantly improve ad campaign performance, resulting in a 43.3% increase in profits. The selected model was Logistic Regression. The insights provided recommendations for personalized content, age-targeted ads, and income-level targeting, enhancing marketing strategy.

Language: Jupyter Notebook - Size: 4.54 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0