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ai-ml-books-cheatsheets

AI ML Books

amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

asrf

Code for ''Alleviating Over-segmentation Errors by Detecting Action Boundaries'' accepted in WACV2021

cornerstone3d-beta

Cornerstone is a set of JavaScript libraries that can be used to build web-based medical imaging applications. It provides a framework to build radiology applications such as the OHIF Viewer.

deep-reinforcement-learning-with-python

Deep Reinforcement Learning with Python, Second Edition, published by Packt

endoslam

EndoSLAM Dataset and an Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner

grounded-segment-anything

Marrying Grounding DINO with Segment Anything & Stable Diffusion & BLIP & Whisper & ChatBot - Automatically Detect , Segment and Generate Anything with Image, Text, and Audio Inputs

jetson-inference

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

medical-data

ml-models

My machine learning models

pyradiomics

Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks. Support: https://discourse.slicer.org/c/community/radiomics

pyscriptannot

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

tensorflow_tuts

My notes from Stanford CS20 Course