Pinned Repositories
Aarif123456
ai_girlfriend
Brain-MRI-Scan-Segmentaion--UNET
This repo consist of the code to segment the MRI SCAN of BRAIN using UNET.
chatopenai
gmail-auto
ppt-creator
Quoraquestionpair
Understand and implementing the real world business problem for Quora if 2 given pair are dublicate or not
Recommendation_Scratch_SGD
reinforment-learning-with-human-feedback
summarization_st
ashishjamarkattel's Repositories
ashishjamarkattel/reinforment-learning-with-human-feedback
ashishjamarkattel/chatopenai
ashishjamarkattel/gmail-auto
ashishjamarkattel/ai_girlfriend
ashishjamarkattel/Brain-MRI-Scan-Segmentaion--UNET
This repo consist of the code to segment the MRI SCAN of BRAIN using UNET.
ashishjamarkattel/ppt-creator
ashishjamarkattel/Quoraquestionpair
Understand and implementing the real world business problem for Quora if 2 given pair are dublicate or not
ashishjamarkattel/Recommendation_Scratch_SGD
ashishjamarkattel/summarization_st
ashishjamarkattel/Aarif123456
ashishjamarkattel/ashishjamarkattel
Config files for my GitHub profile.
ashishjamarkattel/assignment
ashishjamarkattel/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.
ashishjamarkattel/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.
ashishjamarkattel/cicd
ashishjamarkattel/Clustering.
ashishjamarkattel/Dashboard_For_TeddyAI
Dashboard Task using Plotly Dash
ashishjamarkattel/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.
ashishjamarkattel/Language-Translation--Italian-2-English
Repository consist of the code for language translation using Encoder Decoder model
ashishjamarkattel/Mdchat
ashishjamarkattel/mlops
Reading mlops basic
ashishjamarkattel/objectdetection
ashishjamarkattel/PipO
Pileline for training Images using CNN, Transfer learning.
ashishjamarkattel/RedditVideoMakerBot
Create Reddit Videos with just✨ one command ✨
ashishjamarkattel/screenshotReader
ashishjamarkattel/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.
ashishjamarkattel/sentimentbert
ashishjamarkattel/sentimetanalysis
ashishjamarkattel/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.
ashishjamarkattel/Steganography
Implementation of steganography where file will be created by neural network for encoding the message