Topic: feature-scaling Goto Github
Some thing interesting about feature-scaling
Some thing interesting about feature-scaling
feature-scaling,This repository contains a collection of machine learning models and notebooks, primarily focused on the housing dataset. It includes implementations of linear regression, logistic regression, feature scaling techniques, and gradient descent using scikit-learn. Additionally, it features learnings from the University of Washington's ML Specializatio
User: addygeek
feature-scaling,Aplicação de Aprendizado de Máquina (Machine Learning) para o setor de energia. #Previsão #Carga #Geração #Afluentes
User: alexlourencomattos
feature-scaling,Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
User: ashishpatel26
feature-scaling,A curated list of awesome open source and commercial feature store tools and platforms 🚀
Organization: awesome-mlops
feature-scaling,This repository contains all the Machine Learning and Deep Learning projects that I worked on, spans across the two sub domains of Artificial Intelligence i.e., Computer Vision and Text Processing as a part of Machine Learning Nano Degree program at Udacity.
User: bnriiitb
feature-scaling,An introduction into the world of machine learning with a comprehensive Udemy online course, designed for beginners, to learn Python programming fundamentals and gain valuable insights into the practical applications of machine learning.
User: caralifarrell
Home Page: https://www.udemy.com/certificate/UC-630f29d7-9e0e-416a-9404-711893eb5759/
feature-scaling,Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
User: chandradithya8
feature-scaling,Given dataset of Diamonds with features such as Cut, Carat, Clarity etc. I have used libraries such as Pandas, Numpy, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features. Using Scikit-Learn , implemented Algorithms to increase the effective R2 score.
User: chinmayrane16
feature-scaling,Here we make Predictions of car purchase by customer using Machine Learning algorithms.
User: chiragjawale9
feature-scaling,Tutorial on how to perform feature encoding, feature scaling, and missing values imputation using the scikit-learn library
User: chongjason914
feature-scaling,An attempt to predict the Stock Market Price using Long Short Term memory and plot its chart. By tweaking different hyper parameters, we get different trained models. The aim of this project is to identify the relation hidden in these hyper parameters.
User: cyberdevilz
feature-scaling,Improving Machine Learning models performances through Feature Engineering and Feature Scaling techniques such as Principal Component Analysis (PCA), Dummy variables, Standard Scaling and Data Normalization
User: dadavalangege
feature-scaling,A Machine Learning Approach of Emotional Model
User: danyalimran93
feature-scaling,EDA and Feature engineering with Plotly library!
User: ds-brx
feature-scaling,На основании сырых данных с параметрами добычи и очистки золотоносной руды построить прототип модели для предсказания коэффициента восстановления золота из золотоносной руды с лучшей метрикой sMAPE.
User: ejay34
feature-scaling,The purpose of this project is to analyze the impact of climate change on air quality for the city of Austin and create a machine learning model that can establish a correlation between the level of air pollutants like Ozone and NO2 and the climate parameters by using regression models and null hypothesis.
User: esharma3
feature-scaling,The purpose of this project is to predict house prices based of off the Boston house price dataset. The project implements univariate and multivariate linear and polynomial regression models.
User: esharma3
feature-scaling,My solution to House-Prices Advanced Regression Techniques, A beginner-friendly project on Kaggle.
User: gvndkrishna
feature-scaling,This repository is a related to all about Machine Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python), Feature Selection technique in python etc. Follow Coursesteach for more content
User: hussain0048
Home Page: https://coursesteach.com/
feature-scaling,Tutorial- data Pre-processing
User: iamkankan
feature-scaling,Capstone project for Udacity's Intro to Machine Learning Course
User: ian-whitestone
feature-scaling,A Mathematical Intuition behind Linear Regression Algorithm
User: juzershakir
feature-scaling,Machine Learning in Scikit-Learn and TensorFlow
User: katlass
feature-scaling,This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.
User: komal11lamba
feature-scaling,Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree
User: lmego
feature-scaling,Apply unsupervised learning techniques to identify customers segments.
User: manaralharbi
feature-scaling,Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments
User: moreirab
feature-scaling,Machine learning algorithms repository
User: pawangeek
feature-scaling,A series of Jupyter notebooks, to know about Machine Learning, its implementation, and identifying its best practices.
User: pervezsh
feature-scaling,Machine-learning models to predict whether customers respond to a marketing campaign
User: petermchale
feature-scaling,This repo contains Comprehensive notes covering various machine learning concepts, algorithms, and applications, providing a structured resource for both beginners and experienced practitioners to deepen their understanding and proficiency in the field.
User: praj2408
feature-scaling,Data Science Portfolio created for academic and personal projects.
User: prat0101
feature-scaling,This project implements Support Vector Regression (SVR) to predict the salary of an employee based on their position level. The script uses a dataset that contains position levels and corresponding salaries, applying feature scaling to improve the performance of the SVR model. The results are visualized to show how well the model fits the data.
User: qtle3
feature-scaling,Focused on advancing credit card fraud detection, this project employs machine learning algorithms, including neural networks and decision trees, to enhance fraud prevention in the banking sector. It serves as the final project for a Data Science course at the University of Ottawa in 2023.
User: rimtouny
feature-scaling,A collection of working snippets used for machine learning related tasks.
User: risarora
feature-scaling,Machine Learning Notebooks
User: rsc-dev
feature-scaling,Gradient Descent for N features using two datasets: Boston House data, Power Plant Data
User: sabeelahmad
feature-scaling,
User: sakshigupta08
feature-scaling,MLB Team Runs Allowed Prediction Project (Linear Regression)
User: sanghyunkim1
feature-scaling,Applied unsupervised learning techniques on demographic and spending data for a sample of German households.
User: sanjeevai
feature-scaling,Successfully established a machine learning model which can estimate the net health insurance claim of an individual based on a set of characteristics of that individual to an appreciable level of accuracy.
User: sayamalt
feature-scaling,Successfully established a machine learning model which can predict an appropriate stellar class, on the basis of a distinct set of spectral characteristics, to a substantially high level of accuracy.
User: sayamalt
feature-scaling,Tariff is a list of expenses that incur while transporting the goods from one distance to another distance. Tariff is also dependent on seasonal and non-seasonal factors also. This project is aimed at predicting the tariff ratesfor truck load by using the different machine learning algorithms like lasso regression, elastic net regression, ridge regression and linear regression. Tariffisa combination of lot ofthings and tariff rate is dependent on some ofthe factorslikeYear, Road, SeasonalImpact, Fuel Cost,Distance, Weight, Toll charge, Demand, labour cost, travel expenses etc. Using some ofthese factors and by employing the above-mentioned machine learning regression algorithms we will be trying to predict the tariff rates on the trucks. By doing this we can help the industriesto estimate the tariffratesso that they can take the necessary actions and they can make their business run inprofitable way. This model helps small- and large-scale firms to control and manage the cost on transport.
User: shishir349
feature-scaling,The objective of this project is to predication of bike rental count on daily based on the environmental and seasonal settings. As it gets easy for an organisation to arrange the resource if the demand spikes.
User: skynoid2612
feature-scaling,The task is to build a machine learning regression model will predict the number of absent hours. As Employee absenteeism is a major problem faced by every employer which eventually lead to the backlogs, piling of the work, delay in deploying the project and can have a major effect on company finances. The aim of this project is to find an issue which eventually leads toward the absence of an employee and provide a proper solution to reduce the absenteeism
User: skynoid2612
feature-scaling,Karma of Humans is AI
User: the-mrinal
feature-scaling,Exemplary, annotated machine learning pipeline for any tabular data problem.
User: uzaymacar
feature-scaling,This repository is a collection of basic code templates for Data Preparation. All codes I am sharing are from the practical exercises I did from the Data Science Infinity Program.
User: zl63388
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