500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

bahadiryzc

breast-cancer-classi-cation-with-machine-learning

c-hotel-automation

I did mini-hotel automation with C#, and I used Microsoft SQL database for my project. and I want to publish. Hopefully, it will help you with your improve software skills.

covid-19-cases-using-deep-neural-networks-with-x-ray-images

credit-cart-fraud-detection

deep-learning-book

Deep Learning book the covers the principles of deep learning, motivation, explanations, state of the art papers for the various tasks and architectures: CNNs, object detection, semantic segmentation, generative models, denoising, super resolution, style transfer and style manipulation, inpaintig, self supervised learning, vision transformers, OCR, and multi modal. Hope that it will be useful to some of you 🙂

face-mask-detection

Face Mask😷 Detection using TensorFlow

food-101-vision-clasification

gender-detection-using-cnn

google-interview-university

A complete daily plan for studying to become a Google software engineer.

imdb-emotion-analysis-using-rnn

using the deep learning system. The system that controls whether the person likes the movie or not has been developed.

machine-learning-interview-enlightener

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

mias-mammography-object-detection

Detection of tumors on mammography images

production-level-deep-learning

A guideline for building practical production-level deep learning systems to be deployed in real world applications.

rsna-intracranial-hemorrhage-detection

Intracranial hemorrhage, bleeding that occurs inside the cranium, is a serious health problem requiring rapid and often intensive medical treatment. For example, intracranial hemorrhages account for approximately 10% of strokes in the U.S., where stroke is the fifth-leading cause of death. Identifying the location and type of any hemorrhage present is a critical step in treating the patient. Diagnosis requires an urgent procedure. When a patient shows acute neurological symptoms such as severe headache or loss of consciousness, highly trained specialists review medical images of the patient’s cranium to look for the presence, location and type of hemorrhage. The process is complicated and often time consuming. In this competition, your challenge is to build an algorithm to detect acute intracranial hemorrhage and its subtypes. You’ll develop your solution using a rich image dataset provided by the Radiological Society of North America (RSNA®) in collaboration with members of the American Society of Neuroradiology and MD.ai. If successful, you’ll help the medical community identify the presence, location and type of hemorrhage in order to quickly and effectively treat affected patients. Challenge participants may be invited to present their AI models and methodologies during an award ceremony at the RSNA Annual Meeting which will be held in Chicago, Illinois, USA, from December 1-6, 2019.

zero-to-mastery-ml

All course materials for the Zero to Mastery Machine Learning and Data Science course.