saransh09
Data@TUM, Math@DTU, ex-Robotics@FlytBase. Machine Learning, Data Science, Software Engineering, Mathematics.
Munich, Germany
saransh09's Stars
GokuMohandas/Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
GokuMohandas/mlops-course
Learn how to design, develop, deploy and iterate on production-grade ML applications.
upgundecha/howtheysre
A curated collection of publicly available resources on how technology and tech-savvy organizations around the world practice Site Reliability Engineering (SRE)
trimstray/test-your-sysadmin-skills
A collection of Linux Sysadmin Test Questions and Answers. Test your knowledge and skills in different fields with these Q/A.
bregman-arie/devops-exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
binhnguyennus/awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
trimstray/the-book-of-secret-knowledge
A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.
securefederatedai/openfl
An open framework for Federated Learning.
muellerzr/Practical-Deep-Learning-for-Coders-2.0
Notebooks for the "A walk with fastai2" Study Group and Lecture Series
ila/TUM
Notes, material and various stuff collected while attended TUM Master's Degree
eugeneyan/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
daviddwlee84/Stanford-CS224n-NLP
The course notes about Stanford CS224n Natural Language Processing with Deep Learning Winter 2019 (using PyTorch)
data-science-on-aws/data-science-on-aws
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker
mhagiwara/100-nlp-papers
100 Must-Read NLP Papers
visenger/awesome-mlops
A curated list of references for MLOps
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Machine-Learning-Tokyo/papers-with-annotations
Research papers with annotations, illustrations and explanations
maitbayev/the-elements-of-statistical-learning
My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
zhengqigao/PRML-Solution-Manual
My Own Solution Manual of PRML
abhishekkrthakur/mlframework
viraptor/reverse-interview
Questions to ask the company during your interview
VGraupera/1on1-questions
Mega list of 1 on 1 meeting questions compiled from a variety to sources
practical-tutorials/project-based-learning
Curated list of project-based tutorials
piyush6348/Design-Patterns
All design patterns implemented in Java with code, explanation and learning resources
yandexdataschool/nlp_course
YSDA course in Natural Language Processing
yandexdataschool/Practical_RL
A course in reinforcement learning in the wild
jayshah19949596/CodingInterviews
This repository contains coding interviews that I have encountered in company interviews
JuliaLang/julia
The Julia Programming Language
rasbt/deeplearning-models
A collection of various deep learning architectures, models, and tips
andkret/Cookbook
The Data Engineering Cookbook