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dbadeev/README.md

CV

Skills 🛠️

  • Languages: Python, C
  • DS:                NumPy, SciPy, Pandas, Scikit-Learn, Keras, Tensorflow, PySpark
  • Big Data:   Hadoop
  • DevOps:     Docker, Git

Education 🎓

Projects 🐾

Python

  • Computor 1 - Program that solves a polynomial second or lower degree equation and plots the function (including the complex roots of the equation).

     DS

  • Ft Linear Regression - Model implementation that predicts the price of a car depending on it's mileage using a linear regression function trained with a gradient descent algorithm w/o special Libraries and plots the data into a graph
  • Datascience X Logistic Regression - Implementation of multi-classifier model using a logistic regression one-vs-all w/o special Libraries; statistical data analysis; implementation of batch gradient descent, mini-batch gradient descent, stochastic gradient descent; data visualization using different methods
  • Multilayer Perceptron - Implementation of Multilayer Perceptron model with two hidden layers w/o special Libraries
  • Tweets - Sentiment analysis of tweets
  • Churn prediction - Implementation of various models (Naive, RandomForest, Keras, TensorFlow) using NumPy matrix calculations to predict which customers are going to stop being customers of the bank
  • Myspotify - Application of different type algorithms (non-personalized, content-based and collaborative filtering) used for music recommendations
  • City Life - Geospatial analytics based on Taxi Routes and Neighborhoods: GeoPandas, clustering, making maps
  • Understanding customer - Intent classification based on Deep Learning algorithms applied to NLP tasks (RNN, LSTM, BERT, CNN)
  • Uber - Taxi demand forecast based on time series analysis: stationarity, exponential smoothing, SARIMA
  • Amazon - Amazon’s recommender system – “Customers Who Bought This Item Also Bought” using Apache Spark and its 3rd-party libraries
  • Gender Profiling in Social Network - Gender profilng in single and cross genre tweets (Russian language)
  • Summarization of Habr articles - Abstractive summarization of Habr articles using YaGPT

C

  • LIBFT - Rewritten library of C standard functions
  • Fillit - Algorithmic project: Problem of finding a square of the minimum size, in which all the issued tetrimines can be placed without intersections; the solution is based on Knuth's Algorithm X using 'dancing links'
  • Push swap - Algorithmic project: Sorting data on a stack, with a limited set of instructions, using the lowest possible number of actions; the solution is based on  original 'chunks' algorithm
  • Lem-in - Algorithmic project: The goal is to find the quickest way to get N ants across the farm (finding the minimum node-disjoint paths and maximum flow from a source to destination in a nondirected graph); the solution is based on Suurballe's algorithm

DevOps

  • Init - Introduction to System and Network Administration
  • Roger skyline 1 - Virtual Machine installation; the basics about system and network administration; services used on a server machine
  • Docker 1 - The basics for understanding the idea of containerization of services using docker and docker-machine

Security

  • Rainfall - An introduction to the elf-like binary exploitation in i386 system
  • Snow Crash - An introduction to cyber security
  • Over Ride - Next level tasks concerning the elf-like binary exploitation in i386 system after Rainfall project

Certifications 📜

DS

DevOps

Popular repositories Loading

  1. LIBFT LIBFT Public

    Re-writable library of C standard functions

    C

  2. fillit fillit Public

    Цель проекта - разместить заданный набор тетриминок (фигурок тетриса, состоящих из 4 блоков) в квадратной области наименьшей площади так, чтобы тетриминки не пересекались друг с другом (незаполненн…

    C

  3. gender_profiling gender_profiling Public

    Jupyter Notebook

  4. dbadeev dbadeev Public

  5. ft_linear_regression ft_linear_regression Public

    Реализация модели линейной регрессии без использования специальных библиотек для задачи прогнозирования цены автомобиля в зависимости от его пробега; регуляризация; MSE, R-squared statistic; визуал…

    Python

  6. tweets tweets Public

    Цель проекта - анализ тональности твитов. Для сообщений пользователей из тестового набора, необходимо предсказать с максимально возможным результатом, является ли тональность твита положительной, о…

    Jupyter Notebook