Topic: standardscaler Goto Github
Some thing interesting about standardscaler
Some thing interesting about standardscaler
standardscaler,
User: alaa-aleryani
standardscaler,Data Preprocessing for Numeric features (Jupyter Notebook)
User: asharifara
standardscaler,KMeans Clustering of data using Sklearn library, numpy and Pickle data
User: ashirsat96
standardscaler,Correlations, NumPy, Pandas, Seaborn, PCA, Matplotlib, Scatterplot
User: babuttocks
standardscaler,Using the features in the provided dataset, creating a binary classifier that can predict whether applicants will be successful if funded by Alphabet Soup.
User: bharatguturi
standardscaler,T20 World Cup Prediction System -- This GitHub repository contains the code for a T20 World Cup prediction system implemented in Python. The project utilizes popular libraries such as pandas, NumPy, and XGBoost for data manipulation, cleaning, and building predictive models.
User: bramitha-gowda-m
standardscaler,The purpose of the study was to predict if cryptocurrencies can be affected by a 24 hour or 7 day price changes
User: chiomauche
standardscaler,Using LightGBM and Other Models for Car Prices' Prediction – Study Project for Yandex Practicum
User: deleusis
standardscaler,I am on the Advisory Services Team of a financial consultancy. One of MY clients, a prominent investment bank, is interested in offering a new cryptocurrency investment portfolio for its customers. The company, however, is lost in the vast universe of cryptocurrencies. They’ve asked me to create a report that includes what cryptocurrencies are on the trading market and determine whether they can be grouped to create a classification system for this new investment.
User: elliott-dev
standardscaler,Using supervised machine learning to predict credit risk. Trying oversampling, under sampling, combination sampling and ensemble learning to find the model with the best fit
User: emaynard10
standardscaler,Exploring machine learning with nueral networks for a charity analysis. Adjusting the model to try and improve accuracy to predict which projects are likely to be successful.
User: emaynard10
standardscaler,In the digital music era, understanding artist popularity on Spotify is vital. This project taps into Spotify's data, analyzing key factors driving artist prominence. Through our insights, we illuminate what sets successful artists apart in this dynamic platform.
User: gunturwibawa
standardscaler,The main objective of this project was to explore, evaluate and discover valuable insights, by leveraging the power of unsupervised learning to predict if cryptocurrencies are affected by 24-hour or 7-day price changes.
User: helenaschatz
standardscaler,Machine Learning with Scikit Learn
User: iamkirankumaryadav
standardscaler,Predictive Analytics
User: iamkirankumaryadav
standardscaler,An analysis, interpretation, and presentation of what cryptocurrencies are available on the trading market and how they can be grouped using classification. In this project, there are unsupervised learning and Amazon SageMaker skills exhibited by clustering cryptocurrencies and creating plots to present results.
User: jjtiger
standardscaler,NU Bootcamp Module 21
User: jleigh101
standardscaler,The purpose of this project is to predict student loan repayment success using a neural network. Neural networks are computational models inspired by the human brain's structure and function, consisting of layers of interconnected nodes or "neurons" that can learn to recognize patterns in data.
User: jmarihawkins
standardscaler,Using unsupervised learning to predict if crypto currencies are affected by 24-hour or 7-day price changes.
User: kokolipa
standardscaler,Machine Learning clasificación con SKLearn
User: luiggi-piero
standardscaler,
User: manaliagarwal
standardscaler,With the Student Alcohol Consumption data set, we predict high or low alcohol consumption of students.
User: manaliagarwal
standardscaler,Apply unsupervised learning techniques to identify customers segments.
User: manaralharbi
standardscaler,In this project we built a model to predict whether a person will remain in a hypothetical trade union called the United Data Scientists Union (UDSU).
User: marileano
standardscaler,A comprehensive collection of scripts and techniques for efficient data preprocessing in data analysis and machine learning projects.
User: md-emon-hasan
standardscaler,analysis and prediction on ethereum cryptocurrancy dataset through logistic regression model here I used standard scaler to standardized the dataset for better accuracy
User: mk1404
standardscaler,The feature engineering techniques discussed are - dimensionality reduction(pca), scaling(standard scaler, normalizer, minmaxscaler), categorical encoding(one hot/dummy), binning, clustering, feature selection. These are techniques performed on a dataset consisting of Californian House Prices.
User: myliemudaliyar
standardscaler,The principal component analysis is a technique that can transform higher dimensional data into lower dimensional data while keeping the essence of the data Benefits: i) fast execution of the algorithm ii) visualization is easy
User: nani757
standardscaler,Using Unsupervised Machine Learning, an analysis of multiple cryptocurrencies was performed for an investment bank which is in the process of offering crypto as another avenue of investment for customers.
User: nigelrowser
standardscaler,ML / DL Algorithms implemented from scratch. Developed with only numpy as dependency. Machine Learning Algorithms such as Support Vector Machine, Linear Regression, Artificial Neural Networks and other data transformation algorithms are implemented. Project is released as a python package and can be download from Python Package Installer.
User: notshrirang
Home Page: https://pypi.org/project/AgainML/
standardscaler,Electrical_Power_Generation_Prediction
User: palemravichandra
Home Page: https://palemravichandra-electricity-prediction-app-2w2ply.streamlit.app/
standardscaler,Prediction of customer will purchase iPhone or not using KNN classifier model and multiple supervised ML model.
User: pankajvispute
Home Page: http://localhost:8889/notebooks/I_Phone_Purchase_Project_using_KNN_Model.ipynb#
standardscaler,A machine learning exercise using the Spotify "hit predictor" dataset, with data analysis of past "hits" by decade. Deployment using Flask via Heroku.
User: patelpurvip
Home Page: https://spotify-hitpredictor.herokuapp.com
standardscaler,Advertisement Click detection using Kaggle data
User: prakhar2505
standardscaler,In this project, I have developed a Machine Learning model to predict whether users will click on ads. By analyzing various characteristics of users who click on ads, we can gain valuable insights and optimize ad campaigns for better engagement.
User: rahulg-101
standardscaler,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
standardscaler,The project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and face lower risk by tempering potential losses when the market is down.
User: rochitasundar
standardscaler,Data Science - Random Forest Work
User: saikrishnabudi
standardscaler,Module 19 Challenge uses unsupervised machine Learning to predict if Cryptopcurrencies are affected by 24hour or 7day price changes. Normalise data, K-Means Clustering, elbow method and PCA analysis.
User: sandrabotica
standardscaler,Cardiovascular Risk Prediction
User: shaloy-lewis
standardscaler,This is a supervised machine learning project using telecom customer data to predict customers that would churn based on customer Age Group, Relationship Status, Subscribed Services, Charges, and Financial Responsibilities, etc.
User: silaspenda
standardscaler,From Alphabet Soup’s business team, Beks received a CSV containing more than 34,000 organizations that have received funding from Alphabet Soup over the years. Within this dataset are a number of columns that capture metadata about each organization
User: suyinwb
standardscaler,DB-Scan
User: vaitybharati
standardscaler,K-means
User: vaitybharati
standardscaler,pca description and covering its various dimension along with knn
User: vishalanshu
standardscaler,Clustering of the company's clients and a little analytics
User: vonorso
standardscaler,This Jupyter Notebook serves as a comprehensive guide to performing support vector machine (LinearSVC) classification and calculating accuracy scores for machine learning tasks. It provides step-by-step instructions and code examples for building, training, and evaluating a LinearSVC classifier
User: warpedro1
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.