Chaitanya Prakash Bapat's Projects
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Using Hardmax operator in Apache MXNet framework for performing Machine Translation
Temporary repository for MXNet infrastructure code
Model Server for Apache MXNet is a tool for serving neural net models for inference
An interactive book on deep learning. Much easy, so MXNet. Wow.
https://beta.mxnet.io/
Notebooks using the Hugging Face libraries š¤
Numpy main repository
NVIDIA container runtime
The key place for both new members and the tracking of progress by veteran members.
Containerized Data Analytics
Scan, index, and archive all of your paper documents
Goal: make Pattern compatible with Python 3.
List of Hackathon Hackers' personal sites.
NLP project for personalized survey form filling
FHIR-based Mail service that updates the next-of-kin of patients on a daily basis about diagnosis in an interactive manner
Repo for Udacity's Secure & Private AI course
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Protocol Buffers - Google's data interchange format
Seamless operability between C++11 and Python
A Library for Private, Secure, Multi-Owner Deep Learning - Currently Pre Alpha
Mini website crawler to make sitemap from a website.
Apache Spark based price analysis (Part of Big Data Analysis project)
Toolkit for running MXNet training scripts on SageMaker. Dockerfiles used for building SageMaker MXNet Containers are at https://github.com/aws/deep-learning-containers.
A library for training and deploying machine learning models on Amazon SageMaker
Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.
This support code is used for making the TensorFlow framework run on Amazon SageMaker.
Train machine learning models within a š³ Docker container using š§ Amazon SageMaker.