Stars
A curated List of Coding Questions Asked in FAANG Interviews
🖥 Windows Bootable USB creator for macOS. 🛠 Patches Windows 11 to bypass TPM and Secure Boot requirements. 👾 UEFI & Legacy Support
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Sample MLOps Workflow: Recognizing Digits with Kubeflow
The purpose of the catalog is to help data science teams to collect all the requirements to consider while building a ML model and productionizing it.
This repository will take you through creating a FastAPI StableDiffusion app (including Dockerfile) all the way to adding a new feature using industry standard branch development!
Always know what to expect from your data.
Lime: Explaining the predictions of any machine learning classifier
A game theoretic approach to explain the output of any machine learning model.
Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.
Dockerizing an Apache Spark Standalone Cluster
Learn Apache Spark in Scala, Python (PySpark) and R (SparkR) by building your own cluster with a JupyterLab interface on Docker. ⚡
AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
Bulk download your favourite anime episodes from your favourite anime websites
Google Cloud Platform Certification resources.
An easy to use PyTorch to TensorRT converter
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
A reimagined, gesture-controlled car experience. Use hand gestures to control your music, take phone calls, and send slack messages, all from your car. Featured on Google TensorFlow Community Event!
A C++ standalone library for machine learning
The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.
Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activelo…
The fastest path to AI-powered full stack observability, even for lean teams.
The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
The fastai book, published as Jupyter Notebooks
Computer vision container that includes Jupyter notebooks with built-in code hinting, Anaconda, CUDA 11.8, TensorRT inference accelerator for Tensor cores, CuPy (GPU drop in replacement for Numpy),…
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
mlpack: a fast, header-only C++ machine learning library
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.