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W&B Server is the self hosted version of Weights & Biases
Java utilities for manipulating SLS versions
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Banding pattern extraction and banding pattern segmentation mask generation for stained banded chromosome images.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such …
Full reference of LinkedIn answers 2024 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel t…
Open source Structure-from-Motion pipeline
Comparative Evaluation of Hand-Crafted and Learned Local Features
open Multi-View Stereo reconstruction library
A open source structure-from-motion program based on OpenMVG.
List of projects for 3d reconstruction
Python scripts and functions to work with COLMAP
Papers and Datasets about Point Cloud.
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
GANs in computer vision AI Summer article series
COLMAP - Structure-from-Motion and Multi-View Stereo
We well know GANs for success in the realistic image generation. However, they can be applied in tabular data generation. We will review and examine some recent papers about tabular GANs in action.
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
A simple implementation of Batch Normalization using pytorch.
Open source code for AlphaFold.
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
A large-scale face dataset for face parsing, recognition, generation and editing.
AttGAN: Facial Attribute Editing by Only Changing What You Want (IEEE TIP 2019)
Implementation of Skip-GANomaly with MNIST dataset
Tensors and Dynamic neural networks in Python with strong GPU acceleration
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)