Repository Index

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.

AnswerDotAI /nbdev

Jupyter Notebook5.3K514

Create delightful software with Jupyter Notebooks

jupyter-notebooks
python
literate-programming
fastai

lk-geimfari /mimesis

Python4.9K371

Mimesis is a Python library for generating fake but realistic data in multiple languages and locales.

mimesis
fake
data
generator

jupyter-book /jupyter-book

TypeScript4.3K735

Create beautiful, publication-quality books and documents from computational content.

Data-Centric-AI-Community /fg-data-synthetic

Jupyter Notebook1.7K257

Synthetic data generators for tabular and time-series data

gan-architectures
gan
deep-learning
synthetic-data

Athari /YaLinqo

PHP45041

Yet Another LINQ to Objects for PHP [Simplified BSD]

linq
php
functional-programming
query

jeroen /jsonlite

C40447

Simple JSON Parser and Generator for R

Pakillo /grateful

R24421

Facilitate citation of R packages

citation-generator
r
r-package
software-citation

paohaijiao /jquick-pdf

Java2432

JQuick-Pdf is an enterprise-grade Java PDF generation framework. It provides HTML-like declarative syntax and supports more than 30 kinds of graphs, greatly simplifying complex PDF report creation while retaining full native pdfbox(since version 4.0.0) APIs.