The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
-
Updated
May 22, 2024 - Python
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
Free WordPress Plugin: This volume calculator uses a density formula ρ = m/V to find densities of different substances and objects. It calculates the third one for two given values - density, mass, or volume of a substance. www.calculator.io/density-calculator/
Efficient matrix representations for working with tabular data
[ACCV22] Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removal, https://arxiv.org/abs/2210.03061
ML Codefest
CP-APR Tensor Decomposition with PyTorch backend. pyCP_APR can perform non-negative Poisson Tensor Factorization on GPU, and includes an interface for anomaly detection using the extracted latent patterns.
Hand-written-digital-recognition
This repository is dedicated to collecting blog posts and articles on the implementation of state-of-the-art techniques in semantic search, dense retrieval, and retrieval augmented generation (RAG).
Artificial neural networks coded in c++.
I used the MNIST dataset for the implementation of a handwritten digit recognition app. To implement this, will be using a special type of deep neural network called Convolutional Neural Networks. In the end, I also build a Graphical user interface(GUI) where you can directly draw the digit and recognize it straight away.
Implementation of Artificial Neural Networks using NumPy
The main aim of this project is to built a predictive model using G Store data to predict the TOTAL REVENUE per customer that helps in better use of marketing budget.
Intrusion Detection System - IDS example using Dense, Conv1d and Lstm layers in Keras / TensorFlow
Basic_CNN_Implementation
A Fast, Extensible Trainer and Extensions for Pytorch
Add a description, image, and links to the dense topic page so that developers can more easily learn about it.
To associate your repository with the dense topic, visit your repo's landing page and select "manage topics."