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Hospital-Application-
Starting off Creating a hospital application managing diffirent servers (medical,transaction,file) concurrentlyFlask
Staring off with flaskDJ3
SIIM-Iic-Melanoma-classification
Skin cancer is the most prevalent type of cancer. Melanoma, specifically, is responsible for 75% of skin cancer deaths, despite being the least common skin cancer. The American Cancer Society estimates over 100,000 new melanoma cases will be diagnosed in 2020. It's also expected that almost 7,000 people will die from the disease. As with other cancers, early and accurate detection—potentially aided by data science—can make treatment more effective. Currently, dermatologists evaluate every one of a patient's moles to identify outlier lesions or “ugly ducklings” that are most likely to be melanoma. Existing AI approaches have not adequately considered this clinical frame of reference. Dermatologists could enhance their diagnostic accuracy if detection algorithms take into account “contextual” images within the same patient to determine which images represent a melanoma. If successful, classifiers would be more accurate and could better support dermatological clinic work. As the leading healthcare organization for informatics in medical imaging, the Society for Imaging Informatics in Medicine (SIIM)'s mission is to advance medical imaging informatics through education, research, and innovation in a multi-disciplinary community. SIIM is joined by the International Skin Imaging Collaboration (ISIC), an international effort to improve melanoma diagnosis. The ISIC Archive contains the largest publicly available collection of quality-controlled dermoscopic images of skin lesions. In this competition, you’ll identify melanoma in images of skin lesions. In particular, you’ll use images within the same patient and determine which are likely to represent a melanoma. Using patient-level contextual information may help the development of image analysis tools, which could better support clinical dermatologists. Melanoma is a deadly disease, but if caught early, most melanomas can be cured with minor surgery. Image analysis tools that automate the diagnosis of melanoma will improve dermatologists' diagnostic accuracy. Better detection of melanoma has the opportunity to positively impact millions of people.Free-time-Game1-Hangman
pygame hangman # starting off with python game devTreasure-hunt
Wanderer finds Treasure on its ownMachine-Translation
English to French translation over limited dataText-Prediction
IMDB DATASETAnomaly-detection-Ensemble-learning-
Scraping-
Basic Web Scraping of Flipart-IphonesBlogPOst
Blog_Post Proh=jectGreedy
Greedy-Greedy Why are you so needyyyy??Graphs
General Graph problemsflipkart-fashion-tech-sports-data-csv
It is the one way organized way of some scrapped data from online ecommerce webiste flipkartFraud-Detection
Basic implementation of Self-Organizing-mapsBlogger
Ongoing..........Finding-T-for-Treasure
Wanderer "O" will Find Treasure "T" itself...#RLAll_Bout_iMaGe
Unsplash data (image) scraping and image-filtering(Feature Detection)CNN
Cats and Dogs(#simple cnn)AI-BOT-PALYS-ROCK-PAPER-SCISSOR
The ai bot is intelligent enough to win against human with 100% accuracyArchives-CFx001
Archives to some non-trivial problems in category.Rook2D4
recipeMannual-and-shoppingList-Application
Astreak
CoolPalgo
handful of algorithms of my daily endeavour :pPneumonia-chest_xray-detection
Pneumonia detection on chest xray-imagesHandleBars-Templating
Serving files and getting accustomed with Handlebars in Node js-Ang
Angular applicationCodeforces-Parser
Basic parser for parsing inputs and outputs of sample test-cases during contestsRestaurant-System
Restaurant backend application following orders and payment of employees with bonusesFrisby
Deep learning Backend applicationDjango_Unchained-
Another Django Application -- (To do App)Love Open Source and this site? Check out how you can help us