sklearn-library
There are 809 repositories under sklearn-library topic.
transitive-bullshit/scikit-learn-ts
Powerful machine learning library for Node.js – uses Python's scikit-learn under the hood.
heidelbergcement/hcrystalball
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
dadaloop82/MyHomeSmart-HASS-AppDeamon
I have a dream: to give HomeAssistant the ability to reason and perform actions logically and comprehensively, using AppDaemon, Sklearn, and Decision Tree.
wmichalska/EEG-emotions
Application prepares data to learning process. Including preprocessing, cleaning, reformating, feature extraction using PyEEG library and learning using Sklearn tool.
ksachdeva/scikit-nni
AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI
azaz9026/Medicine-Recommendation-System
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
akshaydnicator/Twitter-Sentiment-Analysis-NLP-Hackathon
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.
sid321axn/Detection_of_Malicious_URLs
In this project, we have detected the malicious URLs using lexical features and boosted machine learning algorithms
Findcoding/Android-Malware-Detection-System-Using-Machine-Learning
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.
lihanghang/Enterprise_Credit_Analysis
企业信用分析平台（EEAP）
rochitasundar/Stock-clustering-using-ML
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.
mcabinaya/Bank-Marketing-Data-Analysis
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
GonieAhn/Data-Science-online-course-from-gonie
Data Science - low level to high level
aryanraj2713/Gender-classification
Gender Classification Machine Learning Model using Sk-learn in Python with 97%+ accuracy and deployment
maneprajakta/EXPLORING_SKLEARN
Exploring sklearn 🌟
shridhar1504/Sales-Forecasting-Datascience-Project
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.
syamkakarla98/Linear-Regression
Implementation of Linear regression on Boston House Pricing and Diabetes data sets using python.
nwtgck/multi-svr-python
SVR for multidimensional labels
rudrajikadra/Spam-Classifier-iOS-Application-CoreML-Linear-SVC
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).
Areesha-Tahir/Fake-News-Detection-Using-Naive-Bayes
Fake news detection using Naïve Bayes in Python along with confusion matrix calculated using sklearn.
CG1507/quickcnn
QuickCNN is high-level library written in Python, and backed by the Keras, TensorFlow, and Scikit-learn libraries. It was developed to exercise faster experimentation with Convolutional Neural Networks(CNN). Majorly, it is intended to use the Google-Colaboratory to quickly play with the ConvNet architectures. It also allow to train on your local system.
mahesh147/Decision-Tree-Classifier
Decision Tree Classifier model implemented in a python program.
martandsingh/dataanalytics
Python Data Analytics, Machine Learning & Natural Language Processing
rojaAchary/Data_Preprocessing_Techniques
⚒️ Data preprocessing is the process of transforming raw data into an understandable format. It is also an important step in data mining as we cannot work with raw data. The quality of the data should be checked before applying machine learning or data mining algorithms
undiscovered-genius/Heart-Disease-Prediction-App
❤️ Cardio Guide is an application which uses Machine Learning Model to predict the chances of Heart Disease with an accuracy of 81.967%. With this it also provide you with tips to improve your health status which directly benefits your heart.
abid-mahdi/virtual-personal-trainer
A collection of notebooks for my final year project. The notebooks are used to create a virtual personal trainer to check bicep curls, squats and overhead presses.
Ewenwan/Kaggle
kaggle 比赛 使用sklearn进行kaggle数据竞赛基础及实践
UtsavMurarka/MXene-machine-learning
Classification of MXenes into metals and non-metals based on physical properties
Abhishekmamidi123/Predict-the-damage-to-a-building-ML-Challenge
A Machine Learning challenge #6 - "Predict the damage to a building", organised by Hacker earth. Rank: 242 out of 7540 participants.
srilakshmi-thota/IRIS-DATASET-ANALYSIS-USING-NEURAL-NETWORK
Neural Network with functions for forward propagation, error calculation and back propagation is built from scratch and is used to analyse the IRIS dataset.
nipun-goyal/Residential-Energy-Consumption-Prediction
Predicting the Residential Energy Usage across 113.6 million U.S. households using Machine Learning Algorithms (Regression and Ensemble)
Ranjan2104/Uber-Rides_Prediction-by-using-ML---Flask
Uber Technologies, Inc., commonly known as Uber, is an American technology company. Its services include ride-hailing, food delivery (Uber Eats), package delivery, couriers, freight transportation, and, through a partnership with Lime, electric bicycle and motorized scooter rental. The company is based in San Francisco and has operations in over 900 metropolitan areas worldwide. It is one of the largest firms in the gig economy. so that i Make this Project so company can pred there weekly as well as monthly rides pred that can company help to mange there rides info correctly
Tharun-tharun/AI-Chatbot-Framework-Using-NLTK
A python chatbot framework with Natural Language Understanding and Artificial Intelligence (using NLTK) 💬
Shangamesh2805/HeartDiseasePrediction
Heart disease is a major global health concern that affects millions of people around the world. Early detection and accurate prediction of heart disease can help to prevent the progression of the disease and save lives. In this project, we aim to develop a predictive model for heart disease using various machine learning algorithms.
TanerArslan/Benchmarking_Classifiers_after_SVM-RFE
Evaluating multiple classifiers after SVM-RFE (Support Vector Machine-Recursive Feature Elimination)