In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
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Updated
May 18, 2024
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
An android application to classify 7 different types of skin cancers (images) built by integrating a CNN-RF ensemble Deep Learning model using Kotlin.
Logistic regression is a statistical technique primarily used for binary classification tasks. It predicts the probability of a binary outcome based on one or more predictor variables. Unlike linear regression, which predicts continuous outcomes, logistic regression deals with categorical outcomes.
TensorFlow-powered RESTful API for classifying flower images into five categories.
A Machine Learning Ensemble for Early Blindness Prevention
머신러닝 프레임워크를 활용한 비교사(Unsupervised) 학습 모델 구현 프로젝트
Limited Keyword Speech Recognition using Transfer Learning
A simple Neural Network Model to predict the housing price based on the house features like bedrooms, area, etc. We are using kaggle Housing Prices Dataset. The data has multicollinearity prob
Chainlink's Hackathon Spring 2023
In this project, we 'The Phoenix' will create a model that will help us to predict the stock price, with colorful visualization.
Convolutional Neural Network model- cat/dog classification
Making mosaic art of a given image using tile images generated by a Stable Diffusion model using KerasCV
Computer Vision Game Based on Tensorflow.js and MNIST recognition Model
Learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications
The repository contains an Deep Learning model trained on Alzheimer data for a classification problem
📖 👆🏻 Links Detector makes printed links clickable via your smartphone camera. No need to type a link in, just scan and click on it.
Here i have done CFD Simulation of Airfoil using Ansys ( commercial cfd software ) and OpenFoam (opensource software).
To test if CAPTCHA secure login security codes are secure from bot attacks I developed a CNN classifier model in Python using TensorFlow to predict the CAPTCHA codes. Predicted over 40,000 CAPTCHA codes with an accuracy above 98%.
Pseudo Labelling on MNIST dataset in Tensorflow 2.x
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