Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
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May 1, 2023 - Jupyter Notebook
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Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
python training machine-learning cloud ai deep-learning deployment neural-network tensorflow production deeplearning unet semantic-segmentation machinelearningproject
⭐ ⭐ Use ML to classify flows and packets as benign or malicious. ⭐ ⭐
security data-science machine-learning awesome pcap packet-analyser machinelearning network-analysis hacktoberfest network-security security-tools machine-learning-projects data-science-projects machinelearningproject tcpdump-like infosectools forensics-tools
The Unified Payments Interface (UPI) has revolutionized the way people make payments in India. However, with the increasing adoption of UPI, there has been a rise in fraudulent transactions. To combat this, a UPI fraud detection system Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
code documents finalyearproject computer-science-project real-time-detection machinelearningproject btechproject payment-security upi-fraud-detection computerscienceproject mtechproject
scaffml is a professional ML project structure generator that allows data scientists and ML engineers to quickly scaffold production-ready machine learning projects.
Building a baseline machine learning classifier model to predict whether a customer would clain his/her insurance or not.
machine-learning binary-classification random-forest-classifier machinelearning-python machinelearningprojects machinelearningproject
ganesh kavhar python projects..
github python github-api data-science gitlab machine-learning-algorithms data-visualization gitlab-api machine-learning-library machinelearning learning-by-doing machinelearningprojects ganeshkavharwebsite ganeshkavhargithub ganeshkavharpythontutorials ganeshkavharpypi machinelearningproject ganeshkavharprojects
End to end machine learning deployment project
This repository contains a machine learning project that classifies SONAR reading data to distinguish between rocks and mines. It implements various classification models,evaluates their performance,and features a user-friendly web application deployed with Streamlit for real-time predictions. The project is aimed to help in safe marine operations.
data machine-learning machine-learning-algorithms dataset classification machinelearning prediction-model machinelearning-python machinelearningprojects machinelearningproject streamlit modelevaluation streamlit-webapp modeltraining machinelearningmodel
A school project based on MachineLearning algorithms using pythons and py librairies.
Explainable machine-learning crop recommendation system using soil and environmental conditions with Top-3 predictions, Random Forest, SHAP, and Streamlit.
python data-science machine-learning random-forest agriculture scikit-learn shap machinelearningproject streamlit cropprediction
ScholarIQ is an end-to-end ML project that predicts students' mathematics scores using academic and demographic features. Built with a modular pipeline covering data ingestion, preprocessing, model training and evaluation, Flask integration and deployment on Render. A simple project that taught me how to structure ML projects properly.
python machine-learning linear-regression machine-learning-algorithms machinelearningproject devtown
Complete end to end machine learning project from data scraping to deployment.
football machinelearningproject streamlit-webapp end-to-end-project market-value-prediction football-project
College-Project, A AI Model to predict whether a breast cancer tumor is malignant or benign based on a dataset of cell features from breast tissue.
python machine-learning-algorithms pandas breast-cancer-prediction cancer-detection sklearn-library machinelearningproject aimodel breastcancer
Machine Learning Project - Implemented a machine learning recommender model, which maps a career question from some seeker to appropriate corps.
Missing value imputation using KNN.
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