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Ashish J.kattel's Projects

aws-doc-sdk-examples icon aws-doc-sdk-examples

Welcome to the AWS Code Examples Repository. This repo contains code examples used in the AWS documentation, AWS SDK Developer Guides, and more. For more information, see the Readme.md file below.

cancer-diagnonis icon cancer-diagnonis

Once sequenced, a cancer tumor can have thousands of genetic mutations. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). Currently this interpretation of genetic mutations is being done manually. This is a very time-consuming task where a clinical pathologist has to manually review and classify every single genetic mutation based on evidence from text-based clinical literature. For this competition MSKCC is making available an expert-annotated knowledge base where world-class researchers and oncologists have manually annotated thousands of mutations. We need your help to develop a Machine Learning algorithm that, using this knowledge base as a baseline, automatically classifies genetic variations.

document-classification-cnn icon document-classification-cnn

This repo contains the code for the document classification using conv1d and using the pretrained word embedding vectors. Here we use Glove.

pipo icon pipo

Pileline for training Images using CNN, Transfer learning.

quoraquestionpair icon quoraquestionpair

Understand and implementing the real world business problem for Quora if 2 given pair are dublicate or not

seam-carving icon seam-carving

Technique to resized a images.One of the metrics that we can use is the value of the derivative at each point. This is a good indicator of the level of activity in that neighborhood. If there is some activity, then the pixel values will change rapidly. Hence the value of the derivative at that point would be high. On the other hand, if the region were plain and uninteresting, then the pixel values wouldn’t change as rapidly. So, the value of the derivative at that point in the grayscale image would be low. This thing is called enegry matrix. For each pixel location, we compute the energy by summing up the X and Y derivatives at that point. We compute the derivatives by taking the difference between the current pixel and its neighbors.

spoken-digit-recognization icon spoken-digit-recognization

This repo consist of the analysis and building the model which is able to classify Spoken Digit recognization. The dataset was taken from kaggle. It includes about 4000 wave file which have 0-9 Spoken Digits Where each class 0-9 have around 200 sounds.

steganography icon steganography

Implementation of steganography where file will be created by neural network for encoding the message

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