SamuelaAnastasi

AboutMe

AndroidDataBinding

BakingRecipes

Initial commit

BoundServiceBinderPlayAudio

Audio streaming bound Services example app with Binder implementation.

BuildItBigger

PrivateAI_Challenge_DifferentialPrivacy

Generate Parallel Databases and evaluate The Differential Privacy of a Function using Pytorch

PrivateAi_Challenge_FederatedLearning

Federated Learning with Pysyft Exercises

PrivateAIChallenge_PATE

Differential Privacy for Deep Learning: PATE Analysis

PytorchMNIST_Models

PrivateAI challenge from Facebook and Udacity - Experimenting with Deep Learning Models for MNIST dataset with Pytorch. Played with different Params, Hyperparams and Model Architecture to see the correlation with accuracy and printed statistics. Used Early Stopping and Dropouts techniques to avoid overfitting, with train/validation/test sets.

Sequence_to-Sequence_Models

This projects is an implementation in Pytorch of Sequence-to-Sequence models through LSTM network and Attention Mechanisms. Dataset used is Cornell Movie Dialogs Corpus that basically consists in pairs of dialogs from different movies conversations. The model is trained on preprocessed data to generate its own conversation pairs.

SamuelaAnastasi/Sequence_to-Sequence_Models

This projects is an implementation in Pytorch of Sequence-to-Sequence models through LSTM network and Attention Mechanisms. Dataset used is Cornell Movie Dialogs Corpus that basically consists in pairs of dialogs from different movies conversations. The model is trained on preprocessed data to generate its own conversation pairs.

SamuelaAnastasi/PrivateAI_Challenge_DifferentialPrivacy

Generate Parallel Databases and evaluate The Differential Privacy of a Function using Pytorch

SamuelaAnastasi/PrivateAi_Challenge_FederatedLearning

Federated Learning with Pysyft Exercises

SamuelaAnastasi/PrivateAIChallenge_PATE

Differential Privacy for Deep Learning: PATE Analysis

SamuelaAnastasi/PytorchMNIST_Models

PrivateAI challenge from Facebook and Udacity - Experimenting with Deep Learning Models for MNIST dataset with Pytorch. Played with different Params, Hyperparams and Model Architecture to see the correlation with accuracy and printed statistics. Used Early Stopping and Dropouts techniques to avoid overfitting, with train/validation/test sets.

SamuelaAnastasi/AboutMe

SamuelaAnastasi/Char_Level_LSTM

This project is part of Udacity Computer Vision Nanodegree - Lesson 4 LSTM. The model implements a character-level LSTM with PyTorch. The network will train character by character on some text, then generate new text character by character. This model will be able to generate new text based on the text from the Anna Karenina book.

SamuelaAnastasi/Convolution_Maxpooling

CNN with Pytorch - Show the effects of different filters on a convolution layer before and after maxpooling is applied

SamuelaAnastasi/Custom_kernels_OpenCV

Define and apply different types of High-Pass Low-Pass filters for edge detection and imag blurring with openCV

SamuelaAnastasi/CVND_Convolutional_Filters_Edge_Detection

CVND Convolutional Filters and Edge Detection

SamuelaAnastasi/CVND_Face_Keypoints_Detection

CVND Face Keypoints Detection with OpenCV and ORB Algorithm

SamuelaAnastasi/CVND_FashionMNIST_Classifier

SamuelaAnastasi/CVND_Image_Features_Segmentation

CVND Image Features & Segmentation

SamuelaAnastasi/CVND_LSTM_Networks

SamuelaAnastasi/CVND_Project_Facial_Keypoints_Detection

SamuelaAnastasi/CVND_Project_Image_Captioning

SamuelaAnastasi/CVND_Project_SLAM

SamuelaAnastasi/CVND_Sentiment_Analysis_Projects

SamuelaAnastasi/CVND_Sentiment_Classification

This project is part of Udacity's Computer Vision Nanodegree Extracurricular material study. It builds predictive models for positive/negative opinions on movies reviews dataset.

SamuelaAnastasi/Day_Night_Image_Classifier

Day/Night Image Classifier with OpenCV

SamuelaAnastasi/deep-learning-v2-pytorch

Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101

SamuelaAnastasi/Image_Manipulation_OpenCV

CVND Image manipulation with OpenCV

SamuelaAnastasi/PrivateAiChallenge_SecureFederatedLearning

Private Ai Challenge Facebook Udacity - Secure Federated Learning Exercises

SamuelaAnastasi/PrivateAiChallenge_ToyFederatedLearning

Private AI Challenge project Toy Federated Learning

SamuelaAnastasi/RNN_Sentiment_Analysis

This project is part of Udacity's Course Deep Learning with Pytorch. It uses the power of RNNs implemented through Facebooks's Pytorch framework, to build a model that trains on movies reviews database and performs Sentiment Analysis predictions about positive/negative reviews.

SamuelaAnastasi/Simple_NN_Python

The project builds 2 simple Neural Networks from scratch in Python without use of any Framework.

SamuelaAnastasi/SPAIC_Project_TShirt

This project is part of study groups initiative during Secure and Private Ai Challenge from Udacity and Facebook . The implementation is based on Gaty's neural style transfer paper and uses pretrained models (VGG19) to implement the style transfer from the style image to the content image.

SamuelaAnastasi/UdacityOpenSource

A repository to keep all open sources projects that created by individuals or study groups.

SamuelaAnastasi/works.io

SamuelaAnastasi/YelpMeKnow

YelpMeKnow is a text classifier model, which leverages the power of Google's BERT pretrained models through the Hugging Face Pytorch implementation.