tezzytezzy/bank-account-fraud-analysis

Binary classification model research

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Juussticee/Electrical-Faults-Detection-and-Classification

A project showcasing the use of machine learning in detecting and classifying electrical faults

Language: Python - Size: 60.5 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Sakshikhairnar03/Lung-Cancer-Prediction

The project checks with the users features and then predicts the output

Language: Python - Size: 15.6 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

WasifSohail5/AMUSIC-AI_Powered_MusicRecommendationSystem

AMUSIC is an AI-driven music recommendation system that helps users discover personalized songs. Using Python, Streamlit, and Scikit-learn, it offers smart recommendations, advanced search, and interactive music insights. Users can save favorites, create playlists, and export data for a seamless music discovery experience.

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dimsariyanto/Gold-Price-Prediction

This project predicts gold prices based on historical market data using Bi-LSTM. The model is trained with price and volume features, and evaluated using MAPE to measure prediction accuracy.

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Khushi130404/Titanic_Pipeline

This project predicts whether a person survived the Titanic disaster based on various features using machine learning. It utilizes pipelines, ColumnTransformer, and model serialization for efficient processing and prediction.

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yashmittalz/SFO-Crime-Clustering

Utilizing San Francisco crime data to identify hotspots using K-means clustering techniques.

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EricCroston/COVID-19_Trends

Data Analysis and Visualizations with Python and Pandas

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aneeshmurali-n/Project-ML-Data-Preprocessing

The main objective of this project is to design and implement a robust data preprocessing system that addresses common challenges such as missing values, outliers, inconsistent formatting, and noise. By performing effective data preprocessing, the project aims to enhance the quality, reliability, and usefulness of the data for machine learning.

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venkat-a/Stocks-Price-Analysis-and-Recommendation

Analyzing and predicting the stock prices,multiple machine learning models, including LSTM (Long Short-Term Memory), Prophet, and others

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5hraddha/sentiment-analysis

An innovative system for filtering and categorizing movie reviews

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harishsemwal/Stock-Price-Movement-Prediction

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chinmoyt03/Deep-Learning-Based-Diabetes-Risk-Analysis

Data Science Project: Comparing 3 Deep Learning Methods (CNN, LSTM, and Transfer Learning).

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jha0076/DetectAnamolyML

This is a project to detect anomalies in pump sensor data using One-Class Support Vector Machines (SVM). The data is preprocessed by dropping columns with missing values and scaled using MinMaxScaler. The one-class SVM classifier is trained and used to predict anomalies in the data, which are then saved in a new file "results.csv".

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deva-246/K-Means-Clustering-using-Python-on-Employees-Income-and-Age

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exc-jdbi/MinMaxScalerBytes

A small scaling algorithm for integer sequences.

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IvanSaravanja2306/Credit_Card_Approval_Prediction

Credit Card Approval Prediction based on users' historic data.

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vaitybharati/EDA-1

Exploratory Data Analysis Part-1

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sfansaria/GaussianMixtureModel-Anomaly-Detection

Anomaly Detection Using Gaussian Mixture Model

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OrNixz/predicting-credit-card-approvals

The sixth project from a Data Scientist with Python track by DataCamp

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sreedivyakudupudi/customer_churn

Customer churn prediction using deep learning

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NotShrirang/Machine-Learning-from-Scratch

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.

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suyinwb/Cryptocurrencies

The data Martha will be working with is not ideal, so it will need to be processed to fit the machine learning models. Since there is no known output for what Martha is looking for, she has decided to use unsupervised learning. To group the cryptocurrencies, Martha decided on a clustering algorithm. She’ll use data visualizations to share her findings with the board.

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Priyanshu7129/stock-market-prediction-and-forecasting-using-stacked-LSTM

I have created this project as a part of virtual internship programme offered by LetsGrowMore in data Science.

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Gopinathalpha7/E-Commerce_Customer_Segmentation

[ Analyzing the existing customer data and getting valuable insights about the purchase pattern ] | K-Means clustering | silhouette score | minmaxscalar |

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iamkirankumaryadav/Churn

Customer Churn Prediction

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elifftosunn/RFM-Customers-Analysis

RFM analysis focuses on identifying and segmenting customers based on their purchasing behavior. Analyzed to understand and interact with customers. It can be used together for more effective marketing and customer management strategies.

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lingumd/Cryptocurrencies

Unsupervised machine learning models used to group the cryptocurrencies to help prepare for a new investment.

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nani757/Pipelines

pipelines chains together multiple steps so that the output of each step is used as input to the next step

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shreeratn/Predicting-Credit-Card-Approval

Build a machine learning model to predict if a credit card application will get approved.

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Vineeta12345/KMeans

Performing kmeans clustering and also providing elbow plot

Language: Python - Size: 2.93 KB - Last synced at: over 2 years ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0