Akash's starred repositories
Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
BigDL
Accelerate local LLM inference and finetuning (LLaMA, Mistral, ChatGLM, Qwen, Baichuan, Mixtral, Gemma, etc.) on Intel CPU and GPU (e.g., local PC with iGPU, discrete GPU such as Arc, Flex and Max). A PyTorch LLM library that seamlessly integrates with HuggingFace, LangChain, LlamaIndex, DeepSpeed, vLLM, FastChat, ModelScope, etc.
simple-faster-rcnn-pytorch
A simplified implemention of Faster R-CNN that replicate performance from origin paper
AutoSpotting
Saves up to 90% of AWS EC2 costs by automating the use of spot instances on existing AutoScaling groups. Installs in minutes using CloudFormation or Terraform. Convenient to deploy at scale using StackSets. Uses tagging to avoid launch configuration changes. Automated spot termination handling. Reliable fallback to on-demand instances.
gin-config
Gin provides a lightweight configuration framework for Python
faster_rcnn_pytorch
Faster RCNN with PyTorch
rust-ffi-examples
FFI examples written in Rust
fastprogress
Simple and flexible progress bar for Jupyter Notebook and console
neural-processes
This repository contains notebook implementations of the following Neural Process variants: Conditional Neural Processes (CNPs), Neural Processes (NPs), Attentive Neural Processes (ANPs).
densenet.pytorch
A PyTorch implementation of DenseNet.
pytorch-tvmisc
Totally Versatile Miscellanea for Pytorch
cascade-rcnn_Pytorch
An implementation of Cascade R-CNN: Delving into High Quality Object Detection.
Very-deep-cnn-pytorch
Very deep CNN for text classification
CondenseNet-PyTorch
A PyTorch Implementation for CondenseNet on Cifar10