linear-model
There are 0 repository under linear-model topic.
sberbank-ai-lab / LightAutoML
LAMA - automatic model creation framework
Language:Python 887thundergolfer / Insults
Detect whether a social media comment is insulting or derogatory
Language:Python 23riscy / machine_learning_linear_models
A demo showcasing linear regression, reduced-rank regression and a linear system identification algorithm for modelling time series -- and when to apply them.
Language:Python 17- Language:Python 10
gnu-octave / statistics-resampling
A statistics package with a variety of bootstrap and other resampling tools
Language:MATLAB 9JuliaAI / MLJGLMInterface.jl
MLJ.jl interface for GLM.jl models
Language:Julia 9UmarRajpoot / Identify-Spam-Email-ML-Model
This Model is used to Predict Emails data. Either emails are Spam or Normal (Ham) Mail.
Language:Jupyter Notebook 6- practical-ext-of-intro-stats-in-psy-using-R
rpsystats / practical-ext-of-intro-stats-in-psy-using-R
Practical Extension of Introductory Statistics in Psychology using R
Language:TeX 5 pkiage / tool-credit-risk-modelling
Tool demonstrating building credit risk models
Language:Python 4acpennlab / statistics-resampling
A statistics package with a variety of bootstrap and other resampling tools. This repository is synced to the same-named repository owned by GNU-Octave. It exists to facilitate publication of the developmental version of the statistics-resampling toolbox at MathWorks FileExchange.
Language:MATLAB 2antonio-f / TensorFlow2_digits_classification-Linear_Classifier-MLP
TensorFlow2 digits classification - Linear Classifier and MLP
Language:Jupyter Notebook 2denimamab / PredictHandwrittenDigits
This is a mini project based on two pre-trained models Linear and Convolutional neural networks, and perform predictions in real time according to a draw area where you can draw the digit using the mouse.
Language:Java 2Marvel0usx / Facial-Recognition
Using the logistic regression model to solve some real-world problems, we can explorer different possibilities and outcomes from it.
Language:Jupyter Notebook 2neural-tangjie / NTJ-AIMed_2_Prognosis
:octocat: This repository contains the notes, codes, assignments, quizzes and other additional materials about the course "AI for Medical Prognosis" from DeepLearning.AI Coursera.
Language:Jupyter Notebook 2vaitybharati / Assignment-06-Logistic-Regression
Assignment-06-Logistic-Regression. Output variable -> y y -> Whether the client has subscribed a term deposit or not Binomial ("yes" or "no") Attribute information For bank dataset Input variables: # bank client data: 1 - age (numeric) 2 - job : type of job (categorical: "admin.","unknown","unemployed","management","housemaid","entrepreneur","student", "blue-collar","self-employed","retired","technician","services") 3 - marital : marital status (categorical: "married","divorced","single"; note: "divorced" means divorced or widowed) 4 - education (categorical: "unknown","secondary","primary","tertiary") 5 - default: has credit in default? (binary: "yes","no") 6 - balance: average yearly balance, in euros (numeric) 7 - housing: has housing loan? (binary: "yes","no") 8 - loan: has personal loan? (binary: "yes","no") # related with the last contact of the current campaign: 9 - contact: contact communication type (categorical: "unknown","telephone","cellular") 10 - day: last contact day of the month (numeric) 11 - month: last contact month of year (categorical: "jan", "feb", "mar", ..., "nov", "dec") 12 - duration: last contact duration, in seconds (numeric) # other attributes: 13 - campaign: number of contacts performed during this campaign and for this client (numeric, includes last contact) 14 - pdays: number of days that passed by after the client was last contacted from a previous campaign (numeric, -1 means client was not previously contacted) 15 - previous: number of contacts performed before this campaign and for this client (numeric) 16 - poutcome: outcome of the previous marketing campaign (categorical: "unknown","other","failure","success") Output variable (desired target): 17 - y - has the client subscribed a term deposit? (binary: "yes","no") 8. Missing Attribute Values: None
Language:Jupyter Notebook 2nazaninsbr / Neural-Network-Python
a neural network that classifies handwritten digits
Language:Python 1- Language:C++ 1
QiYuan-Zhang / ModLinear
A wrapped package to linearize the nonlinear continuous/discrete model. Including **numerical** and **symbolic** calculations.
Language:Python 1Splitting data into Linear Model, Exponential, Qaudratic, Additive seasonality , Additive Seasonality Quadratic , Multiplicative Seasonality, Multiplicative Additive Seasonality. Prediction for new time period
Language:Jupyter Notebook 1VibhuJawa / vaccine_prediction
This repo explores tweets and government data related to flu vaccination
Language:Jupyter Notebook 1zeeshanmulla / Admission-Prediction-model
find the chance of admission of a candidate based on his/her GRE Score (out of 340), TOEFL Score (out of 120), rating of the University (out of 5) in which he/she is trying to get admission, Strength of the SOP (out of 5), strength of the Letter Of Recommendation (out of 5), CGPA (out of 10) and the research experience (0 or 1) deployed on GCP
Language:Jupyter Notebook 1admeeer / model_crudeoil
A linear model on NYMEX WTI Crude Oil weekly data that predicts the High and Low of each based on the Open, Close, and Volume.
Language:Jupyter Notebook 0Aurelio-Naufal / Project-Linear-Model-Used-Car-Price-Prediction-Model
Predicting Used Car Price with Linear Model
Language:Jupyter Notebook 0dariga-sm / Disney-Movies-and-Box-Office-Success
Analyze data to see how Disney movies have changed in popularity since its first movie release. Also perform hypothesis testing to see what aspects of a movie contribute to its success.
Language:Jupyter Notebook 0iamcrj / Linear_Regression_In_Python
Simple Linear Regression in Python using Scatter Plot. Update it with your dataset. This code will work for any dependency of form H:X->Y . I have attached a pdf document of my own notes for this model. Feel free to download. Note : The pdf is for help purpose. Any type of reuse or restructuring is subject to copyright.
Language:Python 0melisnv / data-analysis-in-R-programming
R programming and its application to data analysis and statistical methods
Language:R 0Neemias-tech / R-studies
This is a R repository of studies that I made on some data sets. There are linear models, predicition models (boosting - bagging - RandomFlorest), clustering and dendograms.
Language:HTML 0ohmthanap / CS559_Machine-Learning-Fundamentals-Applications
Learned the fundamentals and applications in ML: Intro to Prob. & Linear algebra, Decision Theory, MLE & BE, Linear Model, Linear Discriminant function, Perceptron, FLD, PCA, Non-parametric Learning, Clustering, EM, GMM, EM and Latent Variable Model, Probabilistic Graphical Model, Bayesian Network, Neural Network, SVM, Decision Tree and Boosting
bayesian-estimationbayesian-networkboostingclusteringdecision-theorydecision-treegmmlatent-variable-modelslinear-algebralinear-discriminant-functionlinear-modelmaximum-likelihood-estimationneural-networkpcaperceptronprobabilistic-graphical-modelsprobabilitysupport-vector-machinenon-parametric-learningLanguage:Jupyter Notebook 0r-wisniewski / xG-LinearModel
AHL expected goals linear model in tensorflow
Language:Jupyter Notebook 0Raul-rx7 / Linear_Regression---Happiness_and_Alcohol_Consumption
Estudo de Regressão Linear efetivado a partir do Dataset disponível em <https://www.kaggle.com/marcospessotto/happiness-and-alcohol-consumption>
Language:Jupyter Notebook 0dolremi / Housing_Price
Housing Prediction Kaggle competition https://www.kaggle.com/c/house-prices-advanced-regression-techniques
Language:Jupyter Notebooknishanttomar21 / Sentimental-Analysis
Feedback sentiment analysis (Positive, Neutral, Negative). Applied NLP to automatically identify and extract sentiment. Used Sequential and RNN model for analysis.
Language:Python- Language:Jupyter Notebook
