Clothes style detector, predicts patterns and color together with the clothing category.
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Updated
Jul 23, 2018 - Python
Clothes style detector, predicts patterns and color together with the clothing category.
This repository contains Sentiment Classification, Word Level Text Generation, Character Level Text Generation and other important codes/notes on NLP. Python and Keras are used for implementation.
Implement different Convolutional Neural Networks (CNN) classifiers using GPU-enabled Tensorflow and Keras API Compare different CNN architectures.
Replication of Jasper speech-to-text network using Intel optimized TensorFlow.
Autosuggestion Long Short-Term Memory Recurrent Neural Network model with Keras Functional API
Computer vison based classification model uses deep-learning using Tensorflow2, Keras-API, OpenCV & NLP for Sign Language Recognition.
Analysis of sentiments by training computer neurons :)
Workshop for SMU students, researchers and faculty who need to learn more about Deep Learning using Python Keras API
This Repository contains the most important parts of my Capstone Project. The project was to build and then compare the performance of traditional ML Algorithms to Deep Learning Algorithms on text data. I learned a lot about Natural Language Processing. Compiled all my findings in a 30-page report as well as my power point presentation.
This project is on fine-tuning a Bidirectional Transformers for Language Understanding (BERT) model for text classification with TensorFlow
This repository contains work on Food Dishes Classification from Images, using a truncated version of Food-101 dataset, having 20 categories, using Keras API of TensorFlow in Python.
Keras Functional API implementation of the 50-layer residual neural network (ResNet-50) and its application to sign language digit recognition
Leveraging advanced image processing and deep learning, this project classifies plant images using a subset of the Plant Seedlings dataset. The dataset includes diverse plant species captured under varying conditions. This project holds significance within my Master's in Computer Vision at uOttawa (2023).
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