Marco Cesar Prado Soares's Projects
Use of the Attention architecture (Recurrent Neural Networks - RNN) to create an algorithm for translating English into Portuguese.
Use of the Attention architecture (Recurrent Neural Networks - RNN) to create an algorithm for translating Portuguese into English.
MLB Data Explorer
Implementing Callbacks in TensorFlow using the MNIST Dataset - Basic Image Classification with Deep Learning, in Tensorflow. From the course Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, DeepLearning.AI, Coursera, Week 2 - Introduction to Computer Vision
Application of Bidirectional Recurrent Neural Networks (RNNs) to image classification
Bidirectional RNNs (LSTM) for classification of toxic internet comments
Supporting Information of the paper "Introductory Course in Chemical Engineering: Active Learning Strategies and the Adaptation to the Pandemic"
Redes neurais convolucionais (CNN) para classificação de comentários de internet tóxicos em Google Colab
Image Classification and Object Localization: Convolutional Neural Networks for finding bounding boxes. From the course Advanced Computer Vision with TensorFlow, DeepLearning.AI, Coursera, Week 1 - Concepts in Computer Vision
Use of Convolutional Neural Networks to classify images into 'Cats' or 'Dogs'. From the course Convolutional Neural Networks in TensorFlow, DeepLearning.AI, Coursera, Week 1 - Exploring a Larger Dataset
Use of Convolutional Neural Networks and Tensorflow's ImageDataGenerator to automatically label training data into two classes (happy or sad), and then use of this algorithm to classify face images among these classes. From the course Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, DeepLearning.AI, Coursera, Week 4 - 4. Using Real-world Images
Use of Convolutional Neural Networks and Tensorflow's ImageDataGenerator to automatically label training data into two classes (horses or humans), and then use of this algorithm to classify images among these classes. From the course Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, DeepLearning.AI, Coursera, Week 4 - 4. Using Real-world Images
Use of Convolutional Neural Networks to classify images from the MNIST and Fashion MNIST datasets using Keras and Tensorflow. From the course Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, DeepLearning.AI, Coursera, Week 3 - Enhancing Vision with Convolutional Neural Networks
Use of Convolutional Neural Networks and Image Augmentation to classify images into 'Cats' or 'Dogs'. From the course Convolutional Neural Networks in TensorFlow, DeepLearning.AI, Coursera, Week 2 - Augmentation
Use of Convolutional Neural Networks to classify images from Sign Language MNIST dataset, with hands depicting the 26 letters of the English alphabet. From the course Convolutional Neural Networks in TensorFlow, DeepLearning.AI, Coursera, Week 4 - Multiclass Classifications
Use of Convolutional Neural Networks, Image Augmentation and Transfer learning to classify images into 'Humans' or 'Horses'. From the course Convolutional Neural Networks in TensorFlow, DeepLearning.AI, Coursera, Week 3 - Transfer learning
Defining custom loss functions or objects in TensorFlow. From the course Custom Models, Layers, and Loss Functions with TensorFlow, DeepLearning.AI, Coursera, Week 2 - Custom Loss Functions
Creating custom Callbacks in TensorFlow. From the course Custom Models, Layers, and Loss Functions with TensorFlow, DeepLearning.AI, Coursera, Week 5 - Callbacks
Custom Training in TensorFlow: CV and cancer prediction. From the course Custom and Distributed Training with TensorFlow, DeepLearning.AI, Coursera, Week 2 - Custom Training
Daily temperatures forecasting with CNN-LSTMs deep neural networks. From the course Sequences, Time Series and Prediction, DeepLearning.AI, Coursera, Week 4 - Real-world time series data
10 Weeks, 20 Lessons, Data Science for All!
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Build a Deep and Wide Custom Neural Network in TensorFlow. From the course Custom Models, Layers, and Loss Functions with TensorFlow, DeepLearning.AI, Coursera, Week 4 - Custom Models
A collection of plain text dialogue datasets