Hursh Desai's repositories
must-read-papers-for-ml
Collection of must read papers for Data Science, or Machine Learning / Deep Learning Engineer
covid19-dash
Coronavirus COVID19 US Cases Dashboard
vllm-docker-traefik
vLLM with Traefik for reverse proxy and load balancing
train_ml_with_github_actions
Learn how to do train a simple ML model with Github Actions
deeplearning.ai-mlops-specialization
Deeplearning.ai ML Ops Specialization Course Notes & Notebooks
python-design-patterns
Tutorial on various Python Design Patterns with Examples and Description
Agile_Data_Code_2
Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition
CLIP
Contrastive Language-Image Pretraining
Cloud-GPU-Prep-Tool
Automate's your setup AWS Cloud GPU Windows Server for gaming workstation with themes, widgets and NVIDIA drivers
deep-learning-containers
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
EasyOCR
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
gpt-code-clippy
Full description can be found here: https://discuss.huggingface.co/t/pretrain-gpt-neo-for-open-source-github-copilot-model/7678?u=ncoop57
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
hearst_patterns
Implementation of Hearst patterns for finding hypernym/hyponym pairs using Spacy in Python.
hurshd0.github.io
Personal Website
JHU_IR_Notes
JHU 605.744 Information Retrieval Class Notes
openai-python
The official Python library for the OpenAI API
prefect
The easiest way to automate your data
simple-clock-app
Simple dummy clock app for testing AWS purposes only
terraform-mlops
Helpful terraform scripts for ML infra
testing-and-monitoring-ml-deployments
Example project for the course "Testing & Monitoring Machine Learning Model Deployments"
vllm
A high-throughput and memory-efficient inference and serving engine for LLMs