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NLP-FinHeadlines-MoodTracker is a NLP project utilising sentiment analysis on financial news headlines. It employs a combination of CNN and LSTM layers to predict sentiment (positive, negative, neutral). The model incorporates an embedding layer, 1D convolution, max pooling, bidirectional LSTM, dropout, and dense layer for sentiment classification.

python nlp data-science machine-learning natural-language-processing sentiment-analysis text-classification jupyter-notebook cnn data-visualization lstm dropout data-preprocessing bidirectional-lstm max-pooling 1d-convolution embedding-layer-keras financial-news dense-layers

Updated Jul 14, 2023
Jupyter Notebook

SamaSamrin / Basic-CNN-Implementation

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A beginner-level implementation of the Convolutional Neural Network or CNN, which is an essential algorithm in image processing.

deep-learning neural-network cnn convolutional-neural-networks cnn-keras cifar100 max-pooling

Updated Feb 28, 2023
Jupyter Notebook

lokeshraosaab / Facial_Emotion_Recognition

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Facial Emotion detection involves analysis of images or videos of faces to identify emotions based on the facial expressions

supervised-learning convolutional-neural-networks max-pooling fully-connected-layer

Updated Feb 26, 2024
Jupyter Notebook

aNdr3W03 / Rock-Paper-Scissors-Classification

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Machine Learning For Beginners - Rock, Paper, dan Scissors Image Classification

python machine-learning tensorflow keras image-classification convolutional-neural-networks max-pooling dicoding

Updated Dec 14, 2022
Jupyter Notebook

nazli-d / Binary-Classification-Using-CNN

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This project utilizes a CNN model to classify cat and dog images through training and testing processes. The model is created using the Keras library on the TensorFlow backend.

python opencv tensorflow numpy keras cnn convolutional-neural-networks flatten binary-classification max-pooling sigmoid-function relu-activation cat-and-dog-classifier

Updated Sep 8, 2023
Python

csbanon / mnist-classifiers

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A collection of Jupyter notebooks containing various MNIST digit and fashion item classification implementations using fully-connected and convolutional neural networks (CNNs) built with TensorFlow and Keras. 2020.

computer-vision deep-learning neural-network cnn mnist classification convolution convolutional-neural-network 2d-convolution max-pooling multi-class-classification fully-connected 2d-max-pooling

Updated Nov 12, 2020
Jupyter Notebook

Grace-Hephzibah / Automobile-Parts-Classifier

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A CNN Architecture classifies 14 kinds of automobile parts.

tensorflow matplotlib convolutional-neural-networks data-augmentation adam-optimizer max-pooling dense categorical-cross-entropy

Updated Feb 5, 2023
Jupyter Notebook

cnavneet / DIGICAM

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Digitally recognizing numbers in real life images has been a tough problem in artificial intelligence for many decades. The problem stems from the seemingly endless variations on fonts, colors, spacings, locations etc that these numbers can take within an image.