During my Data Scientist course at SkillFactory I am solving tasks and working on projects. I am presenting the solutions of those tasks and projects as well as auxiliary code here for any potential employers. If you are just interested in data science, please feel free to contact me with any questions.
For the moment the following project on hotel review analysis including data cleaning, exploratory data analysis, building a regression model and evaluating the quality of the model prediciton results, is the most illustrative example of my work:Project-3.Hotel_reviews_analysis.ipynb
In addition I am working on a library of reusable code for data-science purposes: Data Science Helpers
Link: Projects
The goal of the project was to perform data cleaning, exploratory data analysis, build a regression model and evaluate the quality of the model prediciton results. See: Project-3.Hotel_reviews_analysis.ipynb
For more details see: Project-3 -> readme
The goal of the project was to practise SQL knowledge on a database which contained the HeadHunger job openings. Using the SQL queries different analyses should be made revealing the patterns in the data. See: Project-2.HH_Job_openings_analysis.ipynb
For more details see: Project-2 -> readme
The goal of the project was to perform data preparation and clean-up before building a machine learning model. The model should be able to predict a candidate salary based on other candidate attributes. See: Project-1.HH_Resume_analysis.ipynb
For more details see: Project-1 -> readme
Link: Tasks
The goal of the task was to perform basic data cleaning, exploratory data model and building a logistic regression model. Diagrams, parameters and metrics have been logged to Comet ML. See: Task-3.Introduction-to-comet-ml.ipynb
For more details see: Task-3 -> readme
The goal of the task was to perform data cleaning and exploratory data analysis (EDA) on a data set of data science related jobs. The EDA consisted of a visual analysis and of picking and performing statistical tests. See: Task-2.Data_Science_job_analysis.ipynb
For more details see: Task-2 -> readme
The goal of the task was to analyze the bank customers data set and unsing the visual library plotly identify the possible reasons why the customers are exiting their relationship with the bank. See: Task-1.Research_Of_Bank_Customers_Churn.ipynb
For more details see: Task-1 -> readme
Link: Data Science Helpers
In this folder I am collecting auxiliary code for any data science purposes. Currently it contains functions for finding attributes having a certain ratio of empty values, low information attributes and outliers.
For more details see: Data Science Helpers -> readme
In the course of studies I have mastered:
- python
- SQL
- pandas
- numpy
- plotly express
- scipy.stats
- psycopg2
- BeautifulSoup
- git
Dmitriy Golubitskiy | LinkedIn Profile | Codewars Profile