Pranathi Vemuri (pranathivemuri)

pranathivemuri

Geek Repo

Company:CZ BioHub

Location:San Francisco

Home Page:https://www.linkedin.com/in/pranathi-vemuri-ms/

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Pranathi Vemuri's repositories

vessels-ct-radius

2D Skeleton of vessels and radius

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image-segmentation-validation

This repo contains notebook showing grayscale to binary image segmentation and validation

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vispy-example-3d

numpy array volume viewer using vispy

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amazon-sagemaker-examples

Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

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bioconda-recipes

Conda recipes for the bioconda channel.

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Bite-sized-Machine-Learning

Simple example to illustrate machine learning concept

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covid-if-annotations

Annotation Tool for Immunofluorescence Assay Images

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Faster_RCNN_for_Open_Images_Dataset_Keras

Faster R-CNN for Open Images Dataset by Keras

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hover_net

Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.

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hovernet_inference

HoVer-Net inference code for simultaneous nuclear segmentation and classification

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kmermaid

k-mer similarity analysis pipeline.

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Machine-Learning-with-Python

Python code for common Machine Learning Algorithms

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markdown-cheatsheet

Markdown Cheatsheet for Github Readme.md

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napari

napari: a fast, interactive, multi-dimensional image viewer for python

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napari-animation

A napari plugin for making animations

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notion-backup

Simple command to backup a Notion workspace

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paz

Hierarchical perception library in Python for pose estimation, object detection, instance segmentation, keypoint estimation, face recognition, etc.

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rnaseq

RNA sequencing analysis pipeline using STAR, HISAT2 and Salmon with gene counts and quality control

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skeletonization

3D Image Skeletonization Tools

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stardist

StarDist - Object Detection with Star-convex Shapes

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test-datasets

Test data to be used for automated testing with the nf-core pipelines.

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tflite-runtime

Compiled TensorFlow lite runtime. This interpreter-only package is a fraction the size of the full TensorFlow package and includes the bare minimum code required to run inferences with TensorFlow Lite—it includes only the tf.lite.Interpreter Python class. This small package is ideal when all you want to do is execute .tflite models and avoid wasting disk space with the large TensorFlow library.

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tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

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