Prtkk's Stars
uvarc/rivanna-docker
Dockerfiles for Rivanna (Research Computing, University of Virginia)
wsargent/docker-cheat-sheet
Docker Cheat Sheet
chiphuyen/ml-interviews-book
https://huyenchip.com/ml-interviews-book/
openvinotoolkit/anomalib
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
qingsongedu/time-series-transformers-review
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
ashishpatel26/ResourceBank_CV_NLP_MLOPS_2022
This repository offers a goldmine of materials for students of computer vision, natural language processing, and machine learning operations.
jwasham/coding-interview-university
A complete computer science study plan to become a software engineer.
yangshun/tech-interview-handbook
💯 Curated coding interview preparation materials for busy software engineers
MaartenGr/BERTopic
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
youssefHosni/Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
harvardnlp/annotated-transformer
An annotated implementation of the Transformer paper.
maanavshah/stock-market-india
API for Indian Stock Market's NSE and BSE.
ml-tooling/best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Ebazhanov/linkedin-skill-assessments-quizzes
Full reference of LinkedIn answers 2023 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers
orico/www.mlcompendium.com
The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.
deep-learning-with-pytorch/dlwpt-code
Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.
deepset-ai/haystack
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
alexlenail/NN-SVG
Publication-ready NN-architecture schematics.
fchollet/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
groverpr/Machine-Learning
Notes for machine learning
HarisIqbal88/PlotNeuralNet
Latex code for making neural networks diagrams
eugeneyan/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
parulnith/Face-Detection-in-Python-using-OpenCV
Face Detection with Python using OpenCV
FreeBirdsCrew/AI_ChatBot_Python
AI ChatBot using Python Tensorflow and Natural Language Processing (NLP) along side TFLearn
gonzaloplaza/python-weather-forecast
A simple Python console program to get Weather Forecast from DarkSky API using any address as parameter.
rajveermalviya/language-modeling
This is machine learning model that is trained to predict next word in the sequence. Model is defined in keras and then converted to tensorflow-js model for the web, check the web implementation at
Prtkk/From-0-to-Research-Scientist-resources-guide
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.