TuanDDT's starred repositories
Traffic-sign-classification-using-transfer-learning-with-ResNet152V2
Utilizing ResNet152V2 for Traffic Sign Classification: Achieve High Accuracy in Identifying 52 Sign Types with 99% Precision
Image-Processing-with-Python
Open source resources provide examples and sample source code for performing image processing using the Python programming language and OpenCV library. Reliable and accessible resources for learning and practicing image processing with Python.
Transfer-Learning-Use-Inception-v3-For-Image-Classification
Transfer Learning uses Inception v3 to classify human and horse images with 99.39% accuracy.
AgeInMinutes
Enter your date of birth, then the program will show you how many minutes you have lived
Internet-Of-things
project I completed in IOT102 (using arduino uno 3)
Math-project-
Statistics and probability project, Advanced mathematics project
AgeInMinutes2.0
Enter your date of birth, then the program will show you how many minutes you have lived
Using-Word-Embeddings-for-Twitter-Sentiment-Analysis
The project researches sentiment analysis on Twitter, with the goal of evaluating the positivity, negativity or neutrality of comments. Using Word Embeddings, an advanced method in natural language processing, our model achieved a high accuracy of 96.61%. The model was trained on Twitter data and tested on a data comment dataset from Binance.
Using-Support-Vector-Machine-To-Automatically-Take-Class-Attendance
Use the SVM model to automatically take attendance in class with high accuracy up to 80%
Detect-Yoga-Poses-And-Correction-In-Real-Time-Using-Machine-Learning-Algorithms
Compare SVM mode yoga movement classification accuracy with Linear kernel, Polynomial kernel, RBF (Radial Basis Function) kernel, LSTM with accuracy up to 98%. In addition, it also supports adjusting the practitioner's movements according to standard movements.
Use-Google-Play-Scraper-to-crawl-the-Google-Play-Store-for-Python
Use google-play-scraper 1.2.6 to collect app reviews.
Using-deep-learning-to-classify-fruits-using-the-VGG16-model
Classify 8 types of fruit using the VGG16 model with accuracy up to 90%