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bootstrap icon bootstrap

The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.

data-science-ipython-notebooks icon data-science-ipython-notebooks

Recently updated with 50 new notebooks! Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

ds1054z_screen_capture icon ds1054z_screen_capture

Capture the display of a Rigol DS1000Z series oscilloscope by LAN only, using LXI SCPI commands. No USB, no VISA, no IVI and no Rigol drivers are required.

futu_algo icon futu_algo

Futu Algorithmic Trading Framework (Python) 基于富途OpenApi所开发量化高频交易框架

lackey icon lackey

Lackey - Graphical desktop automation with Python

lantern icon lantern

🔴Lantern Latest Download https://github.com/getlantern/lantern/releases/tag/latest 🔴蓝灯最新版本下载 https://github.com/getlantern/forum/issues/833 🔴

minimalmodbus icon minimalmodbus

Easy-to-use Modbus RTU and Modbus ASCII implementation for Python.

modbus icon modbus

Very simple modbus client for STM32 HAL FreeRTOS

phoenix icon phoenix

wxPython's Project Phoenix. A new implementation of wxPython, better, stronger, faster than he was before.

pyftpclient icon pyftpclient

FTP client written in python with monitoring and reconnection

python-scpi icon python-scpi

Since all the other wrappers either require VISA binary or are not generic (and do not implement the device I need)

python-uiautomation-for-windows icon python-uiautomation-for-windows

Python wrapper of Microsoft IUIAutomation. Compatible with py2,py3,x86,x64. Support UIAutomation for MFC, WindowsForm, WPF, Modern UI(Metro UI), Qt, IE, Firefox ...

requests-ftp icon requests-ftp

An FTP transport adapter for use with the Python Requests library.

stockpredictionai icon 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.

tensorflow icon tensorflow

Computation using data flow graphs for scalable machine learning

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