1,603 skills found · Page 21 of 54
neesjanvaneck / Networkanalysis TsTypeScript port of the Java networkanalysis package that provides data structures and algorithms for network analysis.
Tizzzzy / Demonstration Selection Overview✨✨ Official repo for "Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context Learning"
CMU-SAFARI / NATSANATSA is the first near-data-processing accelerator for time series analysis based on the Matrix Profile (SCRIMP) algorithm. NATSA exploits modern 3D-stacked High Bandwidth Memory (HBM) to enable efficient and fast matrix profile computation near memory. Described in ICCD 2020 by Fernandez et al. https://people.inf.ethz.ch/omutlu/pub/NATSA_time-series-analysis-near-data_iccd20.pdf
NhanPhamThanh-IT / Random Forest Wine Quality Prediction🍾 A comprehensive machine learning project using Random Forest algorithm to predict wine quality based on physicochemical properties. Features EDA, model training, hyperparameter tuning, feature importance analysis, and detailed documentation.
itsmnsi / Accenture Pre Onboard LearningAccenture Pre-Onboard Learning Modules Hands-On
sachinjain2000 / Stress Detection Using ML And Image Processing TechniquesThe main motive of our project is to detect stress in the IT professionals using vivid Machine learning and Image processing techniques. Our system is an upgraded version of the old stress detection systems which excluded the live detection and the personal counseling but this system comprises of live detection and periodic analysis of employees and detecting physical as well as mental stress levels in his/her by providing them with proper remedies for managing stress by providing survey form periodically. Our system mainly focuses on managing stress and making the working environment healthy and spontaneous for the employees and to get the best out of them during working hours. The proposed System Machine Learning algorithms like KNN classifiers are applied to classify stress. Image Processing is used at the initial stage for detection, the employee’s image is given by the browser which serves as input. In order to get an enhanced image or to extract some useful information from it image processing is used by converting image into digital form and performing some operations on it. By taking input as an image and output may be image or characteristics associated with that images. The emotion are displayed on the rounder box. The stress level indicating by Angry, Disgusted, Fearful, Sad.
Vu5e / JobFailurePredictionGoogleTraces2019By learning and using prediction for failures, it is one of the important steps to improve the reliability of the cloud computing system. Furthermore, gave the ability to avoid incidents of failure and costs overhead of the system. It created a wonderful opportunity with the breakthroughs of machine learning and cloud storage that utilize generated huge data that provide pathways to predict when the system or hardware malfunction or fails. It can be used to improve the reliability of the system with the help of insights of using statistical analysis on the workload data from the cloud providers. This research will discuss regarding job usage data of tasks on the large “Google Cluster Workload Traces 2019” dataset, using multiple resampling techniques such as “Random Under Sampling, Random Oversampling and Synthetic Minority Oversampling Technique” to handle the imbalanced dataset. Furthermore, using multiple machine learning algorithm which is for traditional machine learning algorithm are “Logistic Regression, Decision Tree Classifier, Random Forest Classifier, Gradient Boosting Classifier and Extreme Gradient Boosting Classifier” while deep learning algorithm using “Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU)” for job failure prediction between imbalanced and balanced dataset. Then, to have a comparison of imbalanced and balanced in terms of model accuracy, error rate, sensitivity, f – measure, and precision. The results are Extreme Gradient Boosting Classifier and Gradient Boosting Classifier is the most performing algorithm with and without imbalanced handling techniques. It showcases that SMOTE is the best method to choose from for handling imbalanced data. The deep learning model of LSTM and Gated Recurrent Unit may be not the best for the in terms of accuracy, based on the ROC Curve its better than the XGBoost Classifier and Gradient Boosting Classifier.
goitacademy / Design And Analysis Of AlgorithmsNeoversity Master's degree
himanshukandwal / Algorithms Design And AnalysisRepository for designing and solving various interesting algorithms
anmoljagetia / Design And Analysis Of AlgorithmsThis repository consists of codes written during my undergraduate Design and Analysis of Algorithms course!
NishkarshRaj / Design And Analysis Of AlgorithmsAlgorithms and Data Structures.
ksatria / MK DAAKumpulan file terkait matakuliah Design Analysis Algorithm STIKOM PGRI Banyuwangi dosen pengampu Khoirul Umam, M.Kom
denopas / ChurnAnalysisCustomer Churn Analysis Experiments using Classical ML algorithms and Deep Neural Network
nishnash54 / TSP ACOTravelling Salesman Problem using Ant Colony Optimization
yunzinan / Solutions To Algorithm Design And Analysis《算法设计与分析（第2版）》黄宇编著 个人题解（部分）
AlexIoannides / Pymc Advi Hmc DemoDemonstrating HMC and ADVI algorithms for Bayesian data analysis using PYMC3.
brightlikethelight / Networkx MCP Server🕸️ First NetworkX MCP server for graph analysis in AI conversations | Community & Enterprise editions | Graph algorithms • Network analysis • MCP integration
JinlongLi2016 / AlgorithmsDesignTechniquesandAnalysis算法设计技巧与分析 课后习题解析 <Algorithms Design Techniques and Analysis>M.H. a1suwaiyel textbook algorithms
sesiria / AlgsExercise for the textbook Data Structures and Algorithm Analysis in C++
HankerZheng / Data Structure And Algorithm In PythonSome basic algorithms and data structures in "Data Structure and Algorithm Analysis in C" by Mark Allen Weiss implementation in Python.
