amit nautiyal's repositories
amitnautiyal.github.io
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ARM_LogicApp
ARM Logic App developed in Visual Studio to create a logic app in Azure and trigger it remotely via VS.
autograd
Efficiently computes derivatives of numpy code.
Awesome-LLM-KG
Awesome papers about unifying LLMs and KGs
awesome-mlops
:sunglasses: A curated list of awesome MLOps tools
awesome-mlops-1
A curated list of references for MLOps
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
awesome-python
A curated list of awesome Python frameworks, libraries, software and resources
cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
d3-shape
Graphical primitives for visualization, such as lines and areas.
dagster
A data orchestrator for machine learning, analytics, and ETL.
Data-Science-Application-Feature-Selection
Feature selection in Data Science Application
Docker-for-Microservices-with-Python
Implementation of Hands-On Docker for Micro services with Python: Design, deploy, and operate a complex system with multiple microservices using Docker and Kubernetes
Fling--LocalAndDistributed
Test a Local Flink Setup and Distributed Flink Installation
haystack
:mag: End-to-end Python framework for building natural language search interfaces to data. Leverages Transformers and the State-of-the-Art of NLP. Supports DPR, Elasticsearch, Hugging Face’s Hub, and much more!
Intel-MachineLearning
Supervised learning algorithms Key concepts like under- and over-fitting, regularization, and cross-validation How to identify the type of problem to be solved, choose the right algorithm, tune parameters, and validate a model
mlxtend
A library of extension and helper modules for Python's data analysis and machine learning libraries.
PlotNeuralNet
Latex code for making neural networks diagrams
stack-drift-notifier-
stack drift notifier for AWS
transformers-forked
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.