achicha's repositories
my-configs
I will store here my configs (docker, sh, cfg)
de_faq
Полезная информация о жизни в Германии
gbdjangoshop
simple shop (Python/Django)
InstaPy
📷 Instagram Like/Comment/Follow Automation Script
jaffle_shop
Data for dbt tutorial
lead-lag
Estimation of the lead-lag parameter from non-synchronous data.
learn-django
learning django projects
machine-learning-for-trading
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
pairstrade-fyp-2019
We tested 3 approaches for Pair Trading: distance, cointegration and reinforcement learning approach.
py_samples
python examples (parsers, flask, aiohttp, angular)
PyTradingGlue
Simple examples how to connect python to almost any trading platform or framework
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.
tseries-patterns
trend / momentum and other patterns in financial timeseries
vogel
PosgreSQL Debezium CDC Example