Irakli Gugushvili

We created a penetration testing platform where the user could run and monitor predefined attacks. The user could create a custom attack manually and test, run, and monitor it. We used Django for the back end, PostgreSQL for the database, 用于部署AWS和单独的异步工具, GCP for bot creation and running, and Elasticsearch for logs.

We developed this system to monitor Azure users' activities using built-in and custom policy combinations to check compliance. In the case of non-compliance, the system would alert the owner to solve it. 如果需要，我们也可以在我方执行. 我们使用Azure逻辑应用程序启动, 执行逻辑的Azure函数, Azure队列存储用于在函数之间进行通信, and Azure Table to save the data.

该系统允许根用户监视子用户的活动. It ran at a time interval, collected sub-users activities, and enforced compliance if needed. We used several lambda functions, SQS for communication, DynamoDB for saving the data, Elasticsearch for logs, Jenkins for CI/CD, 和Terraform的基础设施作为代码.

The project was about creating a recommendation engine for the video streaming platform. 我创造了整个基础设施, 从使用Azure函数的ETL开始, the back-end API using Flask, and finally, 使用Faiss的矢量比较和预测.

We created this website to attach a VPC with an NLB and TG setup to the EC2 instance with no public access. 这样使用服务器要安全得多. I focused mainly on the back end and implemented the entire pipeline of attaching and detaching in AWS Step Functions. 我们在前端使用了带有API网关的React, Jenkins for CI/CD, 和Terraform的基础设施作为代码.

This project consisted of scraping all kinds of publicly available data using Scrapy. I created the pipeline and all the different spiders for different data sources. The main challenge for static websites was parsing different pages; for dynamic websites, 它模拟了加载数据的JavaScript请求. We used Scrapinghub (now Zyte) for deployment and AWS S3 with DynamoDB to save the data.

In this project, I created a data analyzer and prediction system for different kinds of data using various tools. Then I created an API using Flask-RESTful and wrapping the system mentioned above into it.

这是一个书签系统，可以保存url和它们的位置. We accomplished this by using Google's geolocation and weather data that was scraped and analyzed using the IBM text analyzer. 我们使用部署在AWS Elastic Beanstalk上的Flask作为主要技术.

This system can receive an email, parse it, and call different APIs depending on its content. 我们将它部署在AWS上，使用SES进行通知, S3 for saving the emails, RDS for saving logs, 和Lambda用于解析和调用API.

This project focused on scraping the deep web to get medicinal information using Python Scrapy. 我创建并固定了爬行器和管道. 在这个项目中最具挑战性的事情是规模.

This project made it easier to manage university buildings because a large set of equipment constantly updated the building data. I created a database to store all the data and built data analysis mechanisms on top of that to process all the information. I also wrapped all that into a Python Dash web application and deployed it on Heroku.

这个项目分析和分类阿拉伯语语音. 制作它很有挑战性，主要是因为我不会说阿拉伯语. I had to do some extra work to correctly evaluate the different models and understand which was better.

在我的职业生涯中，我创建了许多不同的LinkedIn抓取工具. Some gather personal and company data using advanced search features with the best result filtering. I have also implemented account rotation to avoid bans and automated the process by deploying crawlers on AWS.

I created this sentiment analysis tool to increase the accuracy of stock market price predictions. It checks for tweets, 使用Word2Vec和CNN架构模型对它们进行分析, and outputs the sentiment. 这个项目非常具有挑战性!

我创建了一个股票市场价格预测模型. 然后我添加了使用精益引擎的回溯测试. Finally, I set up an Interactive Brokers (IB) server and created an environment for paper trading (simulation) using the IB Python API.

我创建了一个羽毛球直播比分的刮板, matches, draws, and players, 我在上面建立了一个API. 整个项目在Amazon EC2上进行了调度和部署. 这是我参与过的最大的抓取项目之一.

这对再保险公司来说是一个巨大的项目. 我在c#中添加了完整的再保险功能. The most difficult challenge was understanding the complex insurance logic and creating a reusable code.

In this project, I implemented a BitTorrent protocol that allowed users to create their own torrent clients. This was one of my first projects where I used Python and applied my knowledge of networking.

这是一个用C语言编写的HTTP服务器实现. Working on this project was challenging and interesting because I had to implement almost everything from scratch, 这扩展了我的技术经验.