arebs23 Goto Github PK
Name: Victor Oloyede Aregbede
Type: User
Company: Örebro University
Location: Örebro, Sweden
Name: Victor Oloyede Aregbede
Type: User
Company: Örebro University
Location: Örebro, Sweden
A resource repository for 3D machine learning
This work is based on our paper Exploring Spatial Context for 3D Semantic Segmentation of Point Clouds, which is appeared at the IEEE International Conference on Computer Vision (ICCV) 2017, 3DRMS Workshop.
Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"
ALFRED - A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection with R
📚 Papers and blogs by organizations sharing their work on data science & machine learning in production.
A collection of papers on diffusion models for 3D generation.
A collection of AWESOME things about domian adaptation
awesome grounding: A curated list of research papers in visual grounding
A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites
A comprehensive list of PAPERS, CODEBASES, and, DATASETS on Decision Making using Foundation Models including LLMs and VLMs.
A curated awesome list of Machine Learning Engineering resources. Feel free to contribute! 🚀
B-cos Networks: Alignment is All we Need for Interpretability
Bagua Speeds up PyTorch
In this project, you will evaluate the performance and predictive power of a model that has been trained and tested on data collected from homes in suburbs of Boston, Massachusetts. A model trained on this data that is seen as a *good fit* could then be used to make certain predictions about a home — in particular, its monetary value. This model would prove to be invaluable for someone like a real estate agent who could make use of such information on a daily basis.
In this project, you will employ several supervised algorithms of your choice to accurately model individuals' income using data collected from the 1994 U.S. Census. You will then choose the best candidate algorithm from preliminary results and further optimize this algorithm to best model the data. Your goal with this implementation is to construct a model that accurately predicts whether an individual makes more than $50,000. This sort of task can arise in a non-profit setting, where organizations survive on donations. Understanding an individual's income can help a non-profit better understand how large of a donation to request, or whether or not they should reach out to begin with. While it can be difficult to determine an individual's general income bracket directly from public sources, we can (as we will see) infer this value from other publically available features.
The goal of the project is to classifier different programming languages. The machine Learning model is to classifier 18 different classes of Programming Languages
In this project, you will analyze a dataset containing data on various customers' annual spending amounts (reported in *monetary units*) of diverse product categories for internal structure. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with. Doing so would equip the distributor with insight into how to best structure their delivery service to meet the needs of each customer.
Develop production ready deep learning code, deploy it and scale it
Summaries and notes on Deep Learning research papers
This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 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. 📊📈🎉
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 ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.