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Name: Connor McManigal
Type: User
Bio: UCI Master of Data Science graduate student. Technical skills: Python, R, SQL, Java, Machine Learning, Frequentist and Bayesian Statistics, and Probability.
Name: Connor McManigal
Type: User
Bio: UCI Master of Data Science graduate student. Technical skills: Python, R, SQL, Java, Machine Learning, Frequentist and Bayesian Statistics, and Probability.
Implementation of next fit, first fit, best fit, first fit decreasing, and best fit decreasing bin packing algorithms followed by time and space complexity analysis.
Statistical analysis of potential association between a NBA teamβs number and type of injuries to their record from the 2010-15 seasons. Prediction of 2016 season records given injury types and numbers.
Data analysis aimed at better understanding San Diego County automobile accidents while analyzing various features such as weather and dates from the 2021 year.
Comparing logistic regression, decision tree, random forest, k-nearest neighbors, and SVMs in regard to binary prediction performance metrics.
Training VAE and an Mixed-Loss VAE with normal network traffic, then implementing validation and test steps that fold in the attack traffic to ensure models' reconstruction error satisfactorily separates data at with accuracy. Leveraging Bayesian optimization to tune hyperparameters and testing one anomaly at a time hold out strategy with AUCs.
Leveraging sentiment analysis and data augmentation to recreate recipe scoring algorithm with sparse data. Used MLPs and Gradient Boosting Regressors to compare regression metrics such as RMSE and MSE between raw data and raw data in conjunction with augmented data.
Implementation of MergeSort, QuickSort, InsertionSort, ShellSort, BucketSort, RadixSort, Binary Insertion Sort, and Tim Sort followed by time complexity analysis.
Bidirectional traveling salesman problem using branch and bound depth-first search and stochastic local search followed by a time complexity analysis.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
π Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. πππ
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.