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Google Cloud Platform Certification resources.
All the resources you need to get to Senior Engineer and beyond
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
Explain complex systems using visuals and simple terms. Help you prepare for system design interviews.
This repos contains notebooks for the Advanced Solutions Lab: ML Immersion
A Tutorial for Setting Python Development Environment with VScode and Docker
A web-based tool to view, edit, format, and validate JSON
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Latex code for making neural networks diagrams
Google's Engineering Practices documentation
PyMC educational resources
temok-cse / Python
Forked from TheAlgorithms/PythonAll Algorithms implemented in Python
📄 Awesome CV is LaTeX template for your outstanding job application
Tool for encapsulating, running, and reproducing data science projects
Text and supporting code for Think Stats, 2nd Edition
Text and code for the second edition of Think Bayes, by Allen Downey.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
A Python library that helps data scientists to infer causation rather than observing correlation.
Master the fundamentals of machine learning, deep learning, and mathematical optimization by building key concepts and models from scratch using Python.
"Probabilistic Machine Learning" - a book series by Kevin Murphy
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multi…
In which I put together my thoughts on the practice of data science.
A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
An Open Source Machine Learning Framework for Everyone
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.