snci Goto Github PK

research_public

Quantitative research and educational materials

rmnist

Some examples trained on very reduced versions of the MNIST training set

rnn.wgan

Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"

rnnlm

Recurrent Neural Network Language Modeling (RNNLM) Toolkit

rust-in-replit

The freeCodeCamp Rust In Replit course

rust-standard-library-cookbook

Rust Standard Library Cookbook, published by Packt

s-and-p-500-companies

List of companies in the S&P 500 together with associated financials

sas-python-work

scikit-tensor

Python library for multilinear algebra and tensor factorizations

scotch-player

Demo for a Scotch Article

self-driving-car-sim

A self-driving car simulator built with Unity

sentence-space

Generating gradients, exploring neighborhoods.

sgb

Stanford GraphBase

sgx-hardware

This is a list of hardware which is supports Intel SGX - Software Guard Extensions.

shiny-examples

simple-samples

Minimal Electron applications with ideas for taking them further

sit

Systematic Investor Toolkit

smart-contract-best-practices

A guide to smart contract security best practices

smash

An experimental technique for efficiently exploring neural architectures.

snci.github.io

gh_pages

solidity-experiments

Solidity experiments

sound-machine-electron-guide

Accompanying repository for the Electron guide

spark-deep-learning

Deep Learning Pipelines for Apache Spark

stn_idsia_convnet

An implementation of a convolutional neural network with a spatial transformer

stock-forecasting

Stock closing and opening forecasting using Deep neural network and LSTM(technical indicators included)

stockmarketpredictionswithrnn

The goal of this project was to predict stock market prices using a recurrent neural network. This project was inspired by the Standford paper "Financial Market Time Series Prediction with Recurrent Neural Networks Armando Bernal, Sam Fok, Rohit Pidaparthi December 14, 2012" . Using the Standford paper as a baseline, I was able to improve and beat the accuracy of their model using hyper parameter tuning of my RNN network.

stockprediction

Data and code of my Medium story on stock prediction with TensorFlow

stocks-with-flask

Flask app to view stocks. This app uses a blueprint defined in `blueprints/stock.py` for some of its routing and view logic.

streamlit

Streamlit — The fastest way to build custom ML tools

ta

Technical Analysis Library using Pandas and Numpy