Discover Owaiskhan9654/word2vec Open Source project

Yolo-V7-Custom-Dataset-Train-on-Kaggle

Gene and Primer Sequence Analysis for SARS-CoV-2, EGFR(Non Small Lung Cancer Cell), Influenza DNAs ### How can I check my Oligo primers to ensure there are no significant primer design issues? - The difference between melting temperatures (Tm) of the primers should be less than 5°C. - The GC content should be between 35-80% or equivalent to the product being amplified. - The Delta G value of any self-dimers, hairpins, and heterodimers should be weaker (more positive) than -9.0 kcal/mole. Positive numbers indicate that the actual secondary structure shown will not form at all. - Avoid 3' complementarity between the two primers to prevent primer dimers. The IDT OligoAnalyzer APIs can be used to assess these different criteria for a proposed oligo. #### [Reference](https://sg.idtdna.com/pages/support/faqs/how-can-i-check-my-pcr-primers-using-the-oligoanalyzer-program-to-ensure-there-are-no-significant-primer-design-issues-)

Gene-Sequence-Primer-

This repo contains my achievements and tracks my progress and contributions to open source community

owaiskhan9654

Sony-R.I.S.E-India-Hackathon-3rd-Place-Solution

Recent Sony RISE Research Team India organized and this is my Solution in which I secured 3rd Position. Recommender systems are among the most popular applications of data science today. They are used to predict the "rating" or "preference" that a user would give to an item. In this Challenge I have computed and extracted several Features in order to Build this Hybrid Collaborative Recommender System

Team-PYPI-Blue-sky-challenge-HackerEarth-Hackathon-

Utilizing-BioBERT-for-PICO-Evidence-Summarization

Statistical-Inference-Multivariate-Techniques-Python-Implementation

Python Implementation

Here I am Scraping data from https://www.drivearabia.com/ and this code is in sync with the website currently (FEB 2023).

Web-Scraping-from-Used-Car-website-in-UAE-Region

subject_verb_object_extract

Autogen-Kaggle

Search-using-Corpus-embeddings-Generated-from-Sentence-Transformers-and-BM25-Gene-Score-BRAF-V600E

PelicanV3

CSS

PigeonXT-Custom-Satellite-images-labelling

test222

tests

In BIOASQ TASK 9A total Number of articles present are 15,559,157 which is around 25.6 GB in size and Total Number of MeSH Covered in These articles are 29,369

BIOASQ-Task-9A-Elastic-Search-Indexing

Training-of-EEG-Schizophrenia-Disorder-using-CNN-

Pandas-Profiling-on-Credit-card-lead-prediction-dataset

Search using Attention based Sentence Transformers

Owaiskhan96

Clinical-Trial-Article-Search

PDF_EXTRACTOR

PDF EXTRACTOR

Distilled-Bert-Search-using-Attention-based-Sentence-Transformers

PICO-CLASSIFIER

object-detection-cognitensor

Owaiskhan9654.github.io

JavaScript

Principle-Component-Analysis

Wobb-Text-Based-Image-Recommendation1

PDF-EXTRACTOR-PARSER-For-Client

This code is to understand basics concept of NLP .

Hacker-Earth-India-Automobile-Hackathon-by...Mitsubishi-Co-

Natural-Language-Processing-BASICS-

DigiGene-Live-Feed

Covid-Dashboard

Lux_PM_DATA_Science-INterview-Assignment

All the modules are working fine

Cogniternsor-Project

Lung-Cancer-AI

CSS

Amazon-Business-Research-Analyst-Hiring-Challenge

DigiGene

test

vtest

Networth-Corp-Assignment-Submission-Owais-Ahmad

Pelicanv2

COVID XRAY IMAGE CLASSIFICATION USING DEEP LEARNING TECHNIQUES AND OTHER COMPLEX DEEP NEURAL NETWORKS

COVID-XRAY

This is a visualization of spread of Corona Virus Till 21st may using Pyplot Lib. I have use DataSet from Kaggle . If you want to future data please download it from Kaggle

COVID19_VISUALIZATION

I have taken 2X2 Matrix and tried to implement it explicitly without Linalg.SVD Library. Results are not Exactly same when compared with using Linalg.SVD Library Because of some error.

t6est22

Testing-Singular-Value-Decomposition-SVD

EagleView-Custom-Object-Detection

The-Mad-Dresser-

I have used techniques from NLTK Library and implemented them in this Spam classifier

SMS_SPAM_CLASSIFIER

This Repository is a small API which is created to find the difference in C1 raw and T1 raw. this will ensure that specific Gaussian Peak of width 2 is present in both the signals else it will return all other kind of random signal Data as Inconclusive. Keeping in mind this HTTP API is Specifically created to be integrated into flutter application.

Pelican-API-for-data-Processing-Canary-Global

Deep NNs with large number of parameters are powerful machine learning systems. But overfitting is a serious problem in these networks. These NNs are slow to use, making difficulties to deal with overfitting by combining the predictions of different large NNs at testing time. Dropout could be a technique to manage these problems.

Dropout-in-Neural-Networks

The main idea of this project is of Transfer Learning. Bert large 24 encoder Questions Answering model was fine tuned on specific task of Questions Answering. Currently for Demo purposes it is Hosted on free Heroku platform. Please take a moment to catch up the twisting idea.

BERT-Q-A

In this code I am going to use Movie Reviews text,Amazon Reviews and Restaurants reviews. and I am going to implement bag of word model and develop a model that will help in predicting weather a review is good or bad.

Movies-Product-and-Restaurants-Reviews-implementing-BAG-of-Word-Model

"The System only remembers its history from previous unit of time". I have tried to implement Genotype Evolution Model in python. I have taken the Genotype probability Matrix from the book Modeling and Analysis of Stochastic Systems by V.G Kulkarni .Example 2.14 on page 24.

Discrete-Time-Markov-chains-on-Genotype-Evolution

Happy-Monk

BERT, stands for Bidirectional Encoder Representations from Transformers, is a Neural Network based technique for Natural Language processing pretraining .The breakthrough of BERT is in its ability to train language models based on the entire set of words in a sentence or query (bidirectional training) rather than the traditional way of training on the ordered sequence of words (left to right or combined left to right and right to left). BERT allows the language model to learn word context based on surrounding words rather than just the word that immediately precedes or follows it.

BERT-FINE-TUNING