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data-analysis-of-a-bank-s-telemarketing-campaign

The aim of this project is to analyze the dataset, identify trends and build models that can determine whether a client purchases a long-term deposit based on factors such as gender, age, occupation, previous loans, previous campaign interactions, etc

deforestation_analysis

Image classification model to predict what type of deforestation appears in the images. Objective is early detection of this type of actions in protected lands

denoising-autoencoder-on-the-imdb-dataset

Denoising autoendcoder on sequential domains like the IMDB dateset

disaster-tweets-classification-nlp-

Classifying Twitter tweets using various ML algorithm whether they are about disasters or not to help in expediting emergency responses.

handwritten-digit-classification-using-dnn

Classifying images of handwritten digits usign Deep Nueral Networks

image-classification-cifar-10-dataset-using-cnn

Using the CIFAR-10 dataset that contains 60,000 images in 10 classes. In this project we have built a Convolutional Neural Network to classify the 10 different classes in the dataset

lie-detection-on-psychological-tests

Using 13 datasets from 13 different phycological tests to identify fake answers. Analyse if predictors are unreliable and model dependent.

rnn-transformer-for-sentiment-analysis---imdb-dataset

Using RNN and a Transformer, onthe IMDB dataset that contains the text of some reviews and the sentiment given by their authors (either positive or negative). The input to the RNN is the sequence of words that compose a review, so the learning task consists in predicting the overall sentiment of the review

text-classification-using-neural-networks

Text classification of the AG News subset that containts both a title and an excert of the article, however in this project we have only used the excert as in input for the model

variational-autoencoder-on-the-mnist-dataset