Iterative stochastic gradient descent (SGD) linear regressor with regularization

Last update: Oct 29, 2021

Related tags

Machine Learning SGD-Linear-Regressor

Overview

SGD-Linear-Regressor

Iterative stochastic gradient descent (SGD) linear regressor with regularization

Dataset: Kaggle “Graduate Admission 2” https://www.kaggle.com/mohansacharya/. The dataset contains a number of parameters:
1. GRE Scores (out of 340)
2. TOEFL Scores (out of 120)
3. University Rating (out of 5)
4. Statement of Purpose (out of 5)
5. Letter of Recommendation Strength (out of 5)
6. Undergraduate GPA (out of 10)
7. Research Experience (either 0 or 1)
8. Chance of Admit (ranging from 0 to 1)
SGD solver supports 2D grid search with one dimension being the learning rate α and the other dimension being the regularization weight λ.
The loss (error) in regression is defined as the mean squared error (MSE) between the ground truth values and the regression values.

Owner

Zechen Ma

GitHub Repository

Simulate & classify transient absorption spectroscopy (TAS) spectral features for bulk semiconducting materials (Post-DFT)

PyTASER PyTASER is a Python (3.9+) library and set of command-line tools for classifying spectral features in bulk materials, post-DFT. The goal of th

4 Dec 27, 2022

My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data

kNN-vs-RFR My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data In many areas, rental bikes have been launched to

1 Oct 28, 2021

A flexible CTF contest platform for coming PKU GeekGame events

Project Guiding Star: the Backend A flexible CTF contest platform for coming PKU GeekGame events Still in early development Highlights Not configurabl

14 Dec 15, 2022

Firebase + Cloudrun + Machine learning

A simple end to end consumer lending decision engine powered by Google Cloud Platform (firebase hosting and cloudrun)

8 Aug 16, 2022

ML Kaggle Titanic Problem using LogisticRegrission

-ML-Kaggle-Titanic-Problem-using-LogisticRegrission here you will find the solution for the titanic problem on kaggle with comments and step by step c

3 Oct 23, 2022

Machine Learning for Time-Series with Python.Published by Packt

Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am

124 Dec 28, 2022

Deep Survival Machines - Fully Parametric Survival Regression

Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under

10 Dec 30, 2022

A toolbox to iNNvestigate neural networks' predictions!

iNNvestigate neural networks! Table of contents Introduction Installation Usage and Examples More documentation Contributing Releases Introduction In

1.1k Jan 05, 2023

The code from the Machine Learning Bookcamp book and a free course based on the book

5.5k Jan 09, 2023

Machine Learning approach for quantifying detector distortion fields

DistortionML Machine Learning approach for quantifying detector distortion fields. This project is a feasibility study for training a surrogate model

1 Nov 05, 2021

distfit - Probability density fitting

Python package for probability density function fitting of univariate distributions of non-censored data

187 Dec 30, 2022

Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.

Linear Models Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers. Linear Regression

1 Nov 22, 2021

Cryptocurrency price prediction and exceptions in python

Cryptocurrency price prediction and exceptions in python This is a coursework on foundations of computing module Through this coursework i worked on m

1 Nov 07, 2021

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

177 Sep 02, 2022

Repository for DCA0305, an undergraduate course about Machine Learning Workflows and Pipelines

Federal University of Rio Grande do Norte Technology Center Department of Computer Engineering and Automation Machine Learning Based Systems Design Re

81 Oct 18, 2022

Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models.

Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow scikit-learn's functionality wit

33 Dec 27, 2022

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

6.9k Jan 05, 2023

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

1.3k Dec 22, 2022

PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

6.7k Jan 08, 2023

The Fuzzy Labs guide to the universe of open source MLOps

Open Source MLOps This is the Fuzzy Labs guide to the universe of free and open source MLOps tools. Contents What is MLOps, anyway? Data version contr

352 Dec 29, 2022