Web Crawling & Web Scraping

Fault tolerant, stealthy, distributed web crawling with Pyppeteer

crawler-cluster Distributed, Fault-Tolerant Web Crawling. Multi-process, multiple workers Client process queues tasks in Redis. Worker nodes pull tasks from Redis, execute task, and store results in Redis. Client process pulls results from Redis. Pros: Worker nodes can run on any machine. Add or remove worker nodes at runtime without disrupting the system. Achieves fault-tolerance through process isolation and monitoring. Workers are ran as systemd services, where each service is the smallest possible processing unit (either a single browser with a […]

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GUI

A fast and powerful Graphical User Interface Toolkit for Python

Dear PyGui Dear PyGui is a simple to use (but powerful) Python GUI framework. Dear PyGui is NOT a wrapping of Dear ImGui in the normal sense. It is a library built with Dear ImGui which simulates a traditional retained mode GUI (as opposed to Dear ImGui’s immediate mode paradigm). Dear PyGui is fundamentally different than other Python GUI frameworks. Under the hood, Dear PyGui uses the immediate mode paradigm and your computer’s GPU to facilitate extremely dynamic interfaces. Dear […]

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Tool

A Fast End-to-End Neural Speech Recognition Toolkit

Espresso Espresso is an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch and the popular neural machine translation toolkit fairseq. Espresso supports distributed training across GPUs and computing nodes, and features various decoding approaches commonly employed in ASR, including look-ahead word-based language model fusion, for which a fast, parallelized decoder is implemented. We provide state-of-the-art training recipes for the following speech datasets: Requirements and Installation PyTorch version >= 1.5.0 Python version […]

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Security

An Obfuscation-Neglect Android Malware Scoring System

Quark-Engine Quark-Engine is also bundled with Kali Linux, BlackArch. :shipit: A trust-worthy, practical tool that’s ready to boost up your malware reverse engineering. Why Quark? Android malware analysis engine is not a new story. Every antivirus company has their own secrets to build it. With curiosity, we develop a malware scoring system from the perspective of Taiwan Criminal Law in an easy but solid way. We have an order theory of criminal which explains stages of committing a crime. For […]

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Python

Learn Text Classification With Python and Keras

Imagine you could know the mood of the people on the Internet. Maybe you are not interested in its entirety, but only if people are today happy on your favorite social media platform. After this course, you’ll be equipped to do this. While doing this, you will get a grasp of current advancements of (deep) neural networks and how they can be applied to text. Reading the mood from text with machine learning is called sentiment analysis, and it is […]

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Course

How TensorFlow Works?

Tensor Flow permits the subsequent: Tensor Flow helps you to deploy computation to as a minimum one or extra CPUs or GPUs in a computing tool, server, or mobile device in a completely easy manner. This way the matters may be completed very speedy. Tensor Flow lets you specific your computation as a statistics glide graph. Tensor Flow helps you to visualize the graph using the in-constructed tensor board. You can test and debug the graph very without difficulty. Tensor […]

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Machine Learning

A tutorial on training a DarkNet YOLOv4 model for the CrowdHuman dataset

YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Setup If you are going to train the model on Google Colab, you could skip this section and jump straight to Training on Google Colab. Otherwise, to run training locally, you need to have a x86_64 PC with a decent GPU. For example, I mainly test the code in this repository using a desktop PC with: NVIDIA GeForce RTX […]

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Tool

A toolbox that allows to train and evaluate deep learning models

Ludwig Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on top of TensorFlow. To train a model you need to provide is a file containing your data, a list of columns to use as inputs, and a list of columns to use as outputs, Ludwig will do the rest. Simple commands can be used to train models both locally and in a distributed way, and […]

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Machine Learning

A Python package for multiply imputing missing data using deep learning methods

MIDASpy MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant accuracy and efficiency advantages over other multiple imputation strategies, particularly when applied to large datasets with complex features. In addition to implementing the algorithm, the package contains functions for processing data before and after model training, running imputation model diagnostics, generating multiple completed datasets, and estimating regression models on these datasets. Background and suggested citation For more information on MIDAS, […]

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Command-line Tools

Python3 library for multimedia functions at the command terminal

TERMINEDIA This is a Python library allowing using a text-terminal as a low-resolution graphics output, along with keyboard realtime reading, and a couple utilities enough to enable using a text terminal to run simple 2D games or simply rich terminal apps. The “noveau” factor is that it uses Unicode quarter-character block combinations to effectivelly enable 1/4 character “pixels” in the terminal. It also makes use of 24bit “true” color for text, not limiting itself to the 80’s 8 color palette […]

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