• UpdatedJun 4, 2025
• Jupyter Notebook

Powerful machine learning library for Node.js – uses Python's scikit-learn under the hood.

• UpdatedJul 18, 2025
• TypeScript

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

• UpdatedFeb 21, 2024
• Python

I have a dream: to give HomeAssistant the ability to reason and perform actions logically and comprehensively, using AppDaemon, Sklearn, and Decision Tree.

• UpdatedMay 9, 2022
• Python

Application prepares data to learning process. Including preprocessing, cleaning, reformating, feature extraction using PyEEG library and learning using Sklearn tool.

• UpdatedNov 23, 2020
• Python

A Medicine Recommendation System in machine learning (ML) is a software application designed to assist healthcare professionals and patients in selecting the most appropriate medication based on various factors such as medical history, symptoms, demographics, and drug interactions

• UpdatedApr 26, 2024
• Jupyter Notebook

AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI

• UpdatedDec 8, 2022
• Python

In this project, we have detected the malicious URLs using lexical features and boosted machine learning algorithms

• UpdatedAug 19, 2020
• Jupyter Notebook

Leveraging the power of Machine Learning as a tool, we delve into the realm of app permissions to discern the true nature of applications, whether they harbor malicious or benign intent. By analyzing and predicting based on these permissions, we unlock valuable insights to safeguard users in the digital landscape.

• UpdatedMay 29, 2023
• Jupyter Notebook

Problem Statement: Given the tweets from customers about various tech firms who manufacture and sell mobiles, computers, laptops, etc, the task is to identify if the tweets have a negative sentiment towards such companies or products.

• UpdatedMay 17, 2020
• Python

企业信用分析平台（EEAP）

• UpdatedMay 6, 2019
• Java

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.

• UpdatedJan 20, 2022
• Jupyter Notebook

Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data

• UpdatedJun 5, 2018
• Python

Data Science - low level to high level

• UpdatedFeb 29, 2024
• Jupyter Notebook

Develop a data science project using historical sales data to build a regression model that accurately predicts future sales. Preprocess the dataset, conduct exploratory analysis, select relevant features, and employ regression algorithms for model development. Evaluate model performance, optimize hyperparameters, and provide actionable insights.

• UpdatedJul 14, 2023
• Jupyter Notebook

Implementation of Linear regression on Boston House Pricing and Diabetes data sets using python.

• UpdatedAug 11, 2018
• Python

Exploring sklearn 🌟

• UpdatedJan 24, 2021
• Jupyter Notebook

Gender Classification Machine Learning Model using Sk-learn in Python with 97%+ accuracy and deployment

• UpdatedJun 22, 2022
• Jupyter Notebook

SVR for multidimensional labels

• UpdatedJan 16, 2022
• Python

Building a iOS Application using Apple's Core ML Framework, we will builed a Linear SVC model using sklearn library on the SMS Data, users will type a message on their iPhone and our model will then identify whether the message is a Spam or a Ham (Not spam).

• UpdatedJun 14, 2018
• Swift