269 skills found · Page 3 of 9
aparajitad60 / Stacked LSTM For Covid 19 Outbreak PredictionCoronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, resulting in an ongoing pandemic. Long Short Term Memories(LSTMs) can solve numerous tasks not solvable by previous learning algorithms for recurrent neural networks (RNNs). LSTM is applicable to tasks such as unsegmented, connected handwriting recognition, speech recognition and anomaly detection in network traffic or IDS's (intrusion detection systems). LSTMs can also be efficiently applied for time-series predictions. In this project, its shows a four stacked LSTM network for early prediction new Coronavirus dissease infections in some of the mentioned affected countries (India, USA, Czech Republic and Russia) , which is based on real world data sets which are analyzed using various perspectives like day-wise number of confirmed cases, number of Cured cases, death cases. This attempt has been done to help the concerned authorities to get some early insights into the probable devastation likely to be effected by the deadly pandemic.
gszfwsb / Data WhispererCode for ACL 2025 Main paper "Data Whisperer: Efficient Data Selection for Task-Specific LLM Fine-Tuning via Few-Shot In-Context Learning".
sanjit-bhat / Var CNNCode for the paper "Var-CNN: A Data-Efficient Website Fingerprinting Attack Based on Deep Learning" (PETS 2019)
Dogiye12 / Citizen Complaint Categorization In Environmental AgenciesThe Citizen Complaint Categorization in Environmental Agencies" project generates synthetic environmental complaint data and trains a machine learning model to classify issues like pollution, dumping, and deforestation, enabling agencies to efficiently prioritize and address public environmental concerns.
berrehalbadr / Applied Data Science Course In The Oil And Gas IndustryData science and machine learning are fast-paced emerging technologies across all industries including oil and gas. The oil and gas industry has taken big steps to adopt these technologies to make its exploration and production operations more efficient. This course is tailored for oil and gas industry professionals who are interested to implement data analysis and machine learning in their project development and operations.
HuysmanWang / Deep Learning Aided Porous Media Hydrodynamic Analysis And Three Dimensional ReconstructionThe study of hydrodynamic behavior and water-rock interaction mechanisms is typically characterized by high computational efficiency requirements, to allow for the fast and accurate extraction of structural information. Therefore, we chose to use deep learning models to achieve these requirements. In this paper we started by comparing the image segmentation performance of a series of autoencoder architectures on complex geometries of porous media. The goal was to extract hydrodynamic connectivity channels and the mineral composition of rock samples on SEM (Scanning electron microscopy) data, obtained with a 0.97 accuracy. We then focused on improving the computational efficiency of LBM by using GPU acceleration, which allowed us to rapidly simulate structural flow field features of complex porous media. The results obtained showed that we were able to improve the computational efficiency by a factor of 21 in our device environment. We subsequently employed a SWD-Cycle-GAN technique to migrate sedimentation features to the initial 2D structure slices to reconstruct a 3D (three-dimensional) porous media geometry, that fits the depositional features more closely. Overall, we propose a new method for 3D structure reconstruction and permeability performance analysis of porous media, based on deep learning. The proposed method is fast, efficient and accurate.
Komal01 / Phishing URL DetectionPhishing website detection system provides strong security mechanism to detect and prevent phishing domains from reaching user. This project presents a simple and portable approach to detect spoofed webpages and solve security vulnerabilities using Machine Learning. It can be easily operated by anyone since all the major tasks are happening in the backend. The user is required to provide URL as input to the GUI and click on submit button. The output is shown as “YES” for phishing URL and “NO” for not phished URL. PYTHON DEPENDENCIES: • NumPy, Pandas, Scikit-learn: For Data cleaning, Data analysis and Data modelling. • Pickle: For exporting the model to local machine • Tkinter, Pyqt, QtDesigner: For building up the Graphical User Interface (GUI) of the software. To avoid the pain of installing independent packages and libraries of python, install Anaconda from www.anaconda.com. It is a Python data science platform which has all the ML libraries, Data analysis libraries, Jupyter Notebooks, Spyder etc. built in it which makes it easy to use and efficient. Steps to be followed for running the code of the software: • Install anaconda in the system. • gui.py : It contains the code for the GUI and is linked to other modules of the software. • Feature_extractor.py: It contains the code of Data analysis and data modelling. • Rf_model.py: It contains the trained machine learning model. • Only gui.py is to be run to execute the whole software.
kundajelab / GenomelakeSimple and efficient access to genomic data for deep learning models.
zhongjian-zhang / FederalLearning通过阅读Communication-Efficient Learning of Deep Networks from Decentralized Data与Robust and Communication-Efficient Federated Learning from Non-IID Data两篇论文，复现FedAvg与STC算法，完成LSTM模型+ Shakespeare数据集的字符预测任务
loveboyz / ProteoLizard AlgorithmToolkitAdvanced machine learning algorithms for processing ion-mobility mass spectrometry (IMS-MS) raw data to enable high-throughput, efficient analysis leveraging GPUs and modern hardware.
Hazrat-Ali9 / Brain Tumor Detection Data Science🤢 Brain 🥶 Tumor 🤡 Detection 🙉 Data 🤖 Science 🧑🌾 is a machine 🧑🎤 and deep ✈ learning 🛫 project 🚁 focused on 🚋 the early 🚟 detection of 🚀 brain tumors ⛱ using MRI 🚞 scans It 🏫 leverages 🚝 data workflows 🛼 computer 🛸 vision ⛴ and neural 🎳 networks to ⚽ assist 🥎 healthcare ⚾ professionals 🏀 in accurate 🏈 efficient 🎮 diagnosis
SerdarHelli / MRZ Passport Reader From ImageMRZ Passport Reader from Image is a Python-based tool that automatically detects, segments, and extracts text from the Machine-Readable Zone (MRZ) of passport images. Utilizing deep learning models for segmentation and face detection, alongside EasyOCR for text recognition, it ensures accurate and efficient MRZ data extraction.
ppgranger / Simple Vector DbSimple Vector DB is a lightweight, efficient database for high-dimensional vectors. It supports dynamic operations like insertion, update, deletion, and comparison (cosine similarity, Euclidean distance, dot product) via a RESTful API. Ideal for machine learning, data science, and scientific computing applications.
yangyutu / EfficientPythonEfficient python for data science, machine learning, and software engineering
licongguan / ILM ASSLIterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic Segmentation
sjoshi804 / Sas Data Efficient Contrastive LearningOfficial Code for ICML 2023 Data-Efficient Contrastive Self-supervised Learning
vt-vl-lab / Video Data AugLearning Representational Invariances for Data-Efficient Action Recognition
zj-jayzhang / FedAvgThis is a implemention of FedAvg in paper Communication-Efficient Learning of Deep Networks from Decentralized Data.
ianlini / Feagen(deprecated) A fast and memory-efficient Python data engineering framework for machine learning.
ZPGuiGroupWhu / SudeA scalable manifold learning (SUDE) method that can cope with large-scale and high-dimensional data in an efficient manner
