achicha

achicha

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my-configs

I will store here my configs (docker, sh, cfg)

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de_faq

Полезная информация о жизни в Германии

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gbdjangoshop

simple shop (Python/Django)

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InstaPy

📷 Instagram Like/Comment/Follow Automation Script

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jaffle_shop

Data for dbt tutorial

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lead-lag

Estimation of the lead-lag parameter from non-synchronous data.

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learn-django

learning django projects

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machine-learning-for-trading

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

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pairstrade-fyp-2019

We tested 3 approaches for Pair Trading: distance, cointegration and reinforcement learning approach.

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py_samples

python examples (parsers, flask, aiohttp, angular)

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PyTradingGlue

Simple examples how to connect python to almost any trading platform or framework

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QuikPy

Библиотека-обертка, которая позволяет получить доступ к функционалу Quik из Python

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sl-quant

Companion code for the "Self Learning Quant" blog post

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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.

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tseries-patterns

trend / momentum and other patterns in financial timeseries

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vogel

PosgreSQL Debezium CDC Example

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VPIN

Order flow toxicity; Volume-Synchronized Probability of Informed Trading

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wikiflow

Wikipedia updates streaming, transformation and visualisation

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