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3d-machine-learning

A resource repository for 3D machine learning

3d-semantic-segmentation

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.

addressing-the-topological-defects-of-disentanglement

Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"

alfred

ALFRED - A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

anomalib

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

anomalydetection

Anomaly Detection with R

applied-ml

📚 Papers and blogs by organizations sharing their work on data science & machine learning in production.

arebs23

awesome-3d-diffusion

A collection of papers on diffusion models for 3D generation.

awesome-domain-adaptation

A collection of AWESOME things about domian adaptation

awesome-grounding

awesome grounding: A curated list of research papers in visual grounding

awesome-llm-robotics

A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites

awesome-lm-rl

A comprehensive list of PAPERS, CODEBASES, and, DATASETS on Decision Making using Foundation Models including LLMs and VLMs.

awesome-machine-learning-engineer

A curated awesome list of Machine Learning Engineering resources. Feel free to contribute! 🚀

b-cos

B-cos Networks: Alignment is All we Need for Interpretability

bagua

Bagua Speeds up PyTorch

blog-post

boston-house-price

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.

charity-ml

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.

classification-of-programming-languages

The goal of the project is to classifier different programming languages. The machine Learning model is to classifier 18 different classes of Programming Languages

credit-risk-prediction

credit_risk

customer-segmentation

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.

deep-learning

deep-learning-in-production

Develop production ready deep learning code, deploy it and scale it

deeplearning-papernotes

Summaries and notes on Deep Learning research papers

deeplearning.ai-natural-language-processing-specialization

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

demo-example

document-cleaning