A traffic generator pentesting tool to generate random traffic with random mac

FREE Reverse Engineering Self-Study Course HERE A traffic generator pentesting tool to generate random traffic with random mac and ip addresses in addition to random sequence numbers to a particular ip and port. pip3 install scapy chmod +x traffic-generator sudo ./traffic-generator 127.0.0.1 80 1000 Terms Of Use Do NOT use this on any computer you do not own or are not allowed to run this on. You may NEVER attempt to sell this, it is free and open source. The […]

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Python Basics: Code Your First Python Program

In the previous Python Basics video course, you set up Python on your computer. With Python installed, you’re ready ready to start coding! In this video course, you’ll: Write your first Python program Learn what happens when you run a program with an error Learn how to declare a variable and inspect its value Learn how to write comments This course can be enjoyed alone or as an accompaniment to Python Basics: A Practical Introduction to Python 3. Ready to […]

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Powering the next generation of trustworthy AI in a confidential cloud using NVIDIA GPUs

Cloud computing is powering a new age of data and AI by democratizing access to scalable compute, storage, and networking infrastructure and services. Thanks to the cloud, organizations can now collect data at an unprecedented scale and use it to train complex models and generate insights.   While this increasing demand for data has unlocked new possibilities, it also raises concerns about privacy and security, especially in regulated industries such as  

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Microsoft Translator enhanced with Z-code Mixture of Experts models

Translator, a Microsoft Azure Cognitive Service, is adopting Z-code Mixture of Experts models, a breakthrough AI technology that significantly improves the quality of production translation models. As a component of Microsoft’s larger XYZ-code initiative to combine AI models for text, vision, audio, and language, Z-code supports the creation of AI systems that can speak, see, hear, and understand. This effort is a part of Azure AI and Project Turing, focusing on building multilingual, large-scale language models that support various production […]

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A terminal user interface for searching google

A textual user interface for google.com Prerequisites (❗Read carefully❗) Firstly, you’ll need to install the package Secondly, you’ll need to get google search api key(s) Go to developers.google.com/custom-search/v1/overview Scroll down Click the big blue Get a key button (screenshot]) Make a app if you haven’t already, the name doesn’t matter Click the NEXT button You’ll get an api key You can do the above process as many times as you want. Each api key has a 100 request limit per […]

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A drowsiness detection based on YOLOv5 implementation

This repository consists of a drowsiness detection based on YOLOv5 implementation. You can reach the base repo here 1. Prepared Custom Data Set A custom data set was prepared for this project. Videos were taken from 21 different people in scenarios that could happen while driving. Three different categories were discussed in these videos: normal, yawning and head position. Various light conditions and the use of glasses were taken into account. A total of 63 videos were obtained and labeling […]

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Comparison between Frechet Video Distance implementation from StyleGAN-V and the original paper

In this repo, we demonstrate that the FVD implementation from StyleGAN-V paper is equivalent to the original one when the videos are already loaded into memory and resized to a necessary resolution. The main difference of our FVD evaluation protocol from the paper is that we strictly specify how data should be processed, clips sampled, etc. The problem with the original implementation is that it does not handle: data processing: in which format videos are being stored (JPG/PNG directories of […]

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Hcapcha image collector for artificial intelligence

import hcollector, requests s = requests.session() # s.proxies.update({“http”: “proxy”, “https”: “proxy”}) # Proxies are recommended for bulk collection due to restrictions on requests hcollector.HcaptchaCollector(s, 5).collect(“site key”, “url”) # Ex. ‘4c672d35-0701-42b2-88c3-78380b0db560’, ‘discord.com’    

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Experiments with dependency injection in pipeline steps

This is an experiment to understand if we can write data pipelines in a way that you declare the supporting services that each step required, similar to how FastAPI’s Dependencies function. The manner in which each dependencies would be resolved would depend on its runtime environment, thus supporting pipelines that could run locally or in a cloud-based environment. Additionally, each pipeline step should be able to inform cloud providers of its permission requirements when deployed. Design Interfaces Interfaces serve as […]

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