There are 56 repositories under scikitlearn-machine-learning topic.
Machine learning Guide. Learn all about Machine Learning Tools, Libraries, Frameworks, Large Language Models (LLMs), and Training Models.
My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
Disease Prediction based on Symptoms.
Códigos Python com diferentes aplicações como técnicas de machine learning e deep learning, fundamentos de estatística, problemas de regressão de classificação. Os vídeos com as explicações teóricas estão disponíveis no meu canal do YouTube
This is a machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service. We initially made this project as a requirement for an internship at Indian Servers. We are now making it open to contribution.
This repo aims to contain different machine learning use cases along with the descriptions to the model architectures
Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently trajectories.
Final Year Project on Road Accident Prediction using user's Location,weather conditions by applying machine Learning concepts.
Smart agricultural system to recommend most profitable crops to farmers
Science des Données Saison 5: Technologies pour l'apprentissage automatique / statistique de données massives et l'Intelligence Artificielle
Repository for the Brainhack School 2020 team working with fMRI and ABIDE data to train machine learning models.
A pattern focusing on how to use scikit learn and python in Watson Studio to predict opioid prescribers based off of a 2014 kaggle dataset.
Use Machine Learning to Predict Bank Client's CD Purchase with XGBoost and Scikit Learn in Watson Studio
A Classification Problem which predicts if a loan will get approved or not.
An evaluation of word-embeddings for classification
Uber is interested in predicting rider retention. To help explore this question, they have provided a sample dataset of a cohort of users.
Leaf Disease Detection using Image Processing and Deep Learning
Implemented text analysis using machine learning models to classify movie review sentiments as positive or negative. Built using Python 3.6.1.
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
Sentiment Analysis of product based reviews using Machine Learning Approaches. This is my Final Year B.Tech Project, 2018.
Full Python Programming Tutorials with Focus on artificial intelligence and machine learning
Machine Learning Project using Kaggle dataset
Open source malware detection program using machine learning algorithms on system call traces.
Sensor data of a renowned power plant has given by a reliable source to forecast some feature. Initially the work has done with KNIME software. Now the goal is to do the prediction/forecasting with machine learning. The idea is to check the result of forecast with univariate and multivariate time series data. Regression method, Statistical method.
Identification of handwritten digit from images taken by a OV7670 camera module connected to a Raspberry Pi Pico and a 120x160 TFT LCD display. The Pi Pico running CircuitPython handles everything from image acquisition to post-processing and inference. This code is somewhat experimental, but it is fun to play with. For more information, please visit the project's webpage.
Building Fake News Detection using Angular 6 in the frontend, Node JS in Backend to build API using Express JS and Python Scikit Learn machine learning package for detecting Fake News.
Implementation of several ML models on real-world datasets with detailed explanation in notebooks.
Cheatsheets for data science and machine learning beginners
IEEE "Invited Talk on Deep Learning" 03/02/2018
The project is a simple sentiment analysis using NLP. The project in written in python with Jupyter notebook. It shows how to do text preprocessing (removing of bad words, stop words, lemmatization, tokenization). It further shows how to save a trained model, and use the model in a real life suitation. The machine learning model used here is k-Nearest Neighbor which is used to build the model. Various performance evaluation techniques are used, and they include confusion matrix, and Scikit-learn libraries classification report which give the accuracy, precision, recall and f1- score preformance of the model. The target values been classified are positive and negative review.
It generate C code for microcontrollers from Python with Scikit-learn.