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sent-conv-torch

Text classification using a convolutional neural network.

sent-summary

sentence-transformers

Sentence Embeddings with BERT & XLNet

sentiment-analysis-in-event-driven-stock-price-movement-prediction

Use NLP to predict stock price movement associated with news

sentiment-pcnn

Piecewise CNN implementation for sentiment attitudes extraction task

seq2seq

Minimal Seq2Seq model with Attention for Neural Machine Translation in PyTorch

seq2seq-pytorch

Sequence to Sequence Models with PyTorch

sequence_generation_pytorch

This is an attempt to familiarize myself with PyTorch. In this example, the target to generate a sequence of continuous data (sine waves or mix of them) using LSTM

siggraph2017_inpainting

Code for the paper 'Globally and Locally Consistent Image Completion'. http://hi.cs.waseda.ac.jp/~iizuka/projects/completion/

signature-verification-using-deep-learning

Using SigComp'11 dataset for signature verification

simple-faster-rcnn-pytorch

A simplified implemention of Faster R-CNN with competitive performance

simpy

A python library that takes in an optimization problem in a specific format in a text file.It then parses that file and finds the optimization paramaters following the simplex method of optimization.

sklearn-pandas

Pandas integration with sklearn

sling

SLING - A natural language frame semantics parser

som-tsp

Solving the Traveling Salesman Problem using Self-Organizing Maps

spark-ai-summit-2020-text-extraction

spotlight

Deep recommender models using PyTorch.

srcnn-keras

srcnn-pytorch

PyTorch implementation of Image Super-Resolution Using Deep Convolutional Networks (ECCV 2014)

ssd_keras

Port of Single Shot MultiBox Detector to Keras

stanford-cs-221-artificial-intelligence

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

stanford-cs-230-deep-learning

VIP cheatsheets for Stanford's CS 230 Deep Learning

stargan

Official PyTorch Implementation of StarGAN - CVPR 2018

starspace

Learning embeddings for classification, retrieval and ranking.

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stock-predictor

Listens for Stock news on Twitter, performs sentiment analysis by mining information from an online news source, performs supervised predictive modeling and suggests buy or sell decisions of the stock. Computes portfolio returns over time.

stock_price_predication

I have implemented Recurrent Neural Network (RNN model) to predict the future stock prices and compare it with linear regression.

stockmarketgan

Stock Market Prediction Using Unsupervised Features

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.