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batch_examples

Batch_Examples

blog_stuff

experiments and snippets used on the blog

brat-embedded-visualization-examples

minimal examples of brat annotation visualizations

cexamples

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

cnn-text-classification

Text classification with Convolution Neural Networks on Yelp, IMDB & sentence polarity dataset v1.0

confusion_matrix

Contains cf_matrix.py file with a function to make a pretty visualization of a confusion matrix.

context-aware-clustering

Context-aware clustering of mixed/categorical data using word embeddings from Stanford's GloVe and t-SNE (for dimensionality reduction) with the k-means clustering algorithm. This serves as the code and implementation for the paper: Context-aware Clustering using Glove and k-Means

coursera-deep-learning

Solutions to all quiz and all the programming assignments!!!

csharp_scripts

CSharp Snippets in CSX Form

csharpprojects

CSharpProjects

cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

detours_win32_printing

docker-celery-flower

Minimum docker/fastapi/celery/flower setup

docker-flask-celery

Running a flask app and celery worker in the same docker container.

docker-flask-celery-redis

Docker-Compose template for orchestrating a Flask app with a Celery queue using Redis

docker_examples

dockerized-flask-celery-rabbitmq-redis

elasticsearch

fine-tuning-bert

flask-celery-docker-redis

Integrating Flask API backend with Celery for long running tasks

flaskbootstrap4

flaskbootstrap5_crud

flaskexamples

gdi_printing_and_graphics

generative-ai

This repository contains example notebooks and other helpful resources for generative AI workloads running on Dell infrastructure both on prem or in the public cloud. Resources in this repository are for demo purposes only.

getting-things-done-with-pytorch

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

ghostpdl

githubexamples

gpunotes