Volodymyr S. Profile

5.0

(122 レビュー)

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$30 USD / 時間

slavutych,

ukraine

$30 USD / 時間

こちらは現在6:44 午前です

登録日: 12月 4, 2016

22 推薦

Volodymyr S.

@vladishat

5.0

(122 レビュー)

6.7

93%

$30 USD / 時間

slavutych,

ukraine

$30 USD / 時間

99%

完了したプロジェクト

93%

予算内

95%

期限内

23%

再採用率

Data Science and Financial Mathematics Expert

Coherent professional with a problem-solving mentality accompanied by many years of researching and teaching experience in Ukrainian universities. With superior quality in data modeling and simulation, I am confident my work will exceed expectations [login to view URL] Specializing in: - Projects pertaining to Statistical/Data Analysis, Machine Learning, Mathematics, and Physics. - Open AI machine learning and natural language processing (NLP) techniques to analyze documents and respond user queries in a chatbot. - Consulting Businesses through Financial/Inventory/Customer Data Analysis and Forecast. Skills that pertain to this project are the following: - Excellent Communicator - Problem-solver - Attention to detail - Analytical Thinker Analysis Skills: - Multivariate Statistical Analysis - Regression Analysis - Factor Analysis & Sensitivity Analysis - Bayesian Analysis - Monte Carlo Analysis - Experimental Designs - Time Series Analysis - Forecasting - Statistical Quality Control - Spatial Data Analysis - Structural Equation Modeling. Program Proficiency: - Python - R programming - Rapidminer - Matlab - Microsoft Excel. I do not outsource my work; I am a one-man team. Mostly available from 9:00 to 19:00 GMT+2

全て見る R Programmers 、 Ukraine

仕事についてVolodymyr S.に連絡する

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ポートフォリオ

This OpenAI Chatbot answers 'Telegram' messenger client querries about a set custom documents. Basing an LLM, the bot searches similar questions in a set of FAQ and provides the best Q&A if the rate is greater than a low limit threshold. If it lesser than a high limit threshold then the bot provides three optional answers resulting by OpenAI embedding models.

The project interface provideі an access to Open AI ChatGPT for any user of Telegram. The bot is active when my Python code runs on a PC connected to Internet.

Pros:
- No needs to get account and communicate with Open AI ChatGPT directly,
- Access to ChatGPT via Telegram account in any country.
Cons:
- the code must be running on your PC connected to Internet.

Demo is available at https://t.me/DoConsultBot

AI Chatbot on custom documents

This application estimates the high-frequency trading (HFT) profitability by analyzing Bids and Asks frequencies and optimizing P&L.
The application reads preliminary stored Binance an hour ticks history file of the selected symbol (click Choose Symbol to get it) and Fee (click Set Fee).
Available at: https://skipper.shinyapps.io/shiny_asset_assess/

High-Frequency Trading profitability

This Shiny Web application is available at https://skipper.shinyapps.io/sales_forecast/). It reads and summaries the history of sales, trains a predictive model, and makes a forecast for the chosen number of days. The source of the data is a net of shops and stores SQLite database.

Package ‘prophet’ is used to build the model and forecast. This is a very successful procedure which is based on an additive (or multiplicative) model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus (optional) holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.

Sales Forecast (Shops & Stores Net)

This Warehouse Dashboard application implements Market Basket Analysis to mine the relationship between different products. It uses 'arules' package for getting rules and 'flexdashboard' package for Shiny.
https://skipper.shinyapps.io/shiny_warehouse_dashboard/?fbclid=IwAR14xXF60oytz55Vn-wcvMiDYsy_ky3kvKuVyj8o5OswEOuOeiMEBbLOHr4

The app tries to read the file 'data.zip' with 'data.csv' inside, if it exists in the working directory. Alternatevely, you may choose a local CSV-file that contains the columns: 'Date' (as yyyy-mm-dd), 'OrderID', 'ProductID', 'CustomerID', and 'Qty.Logged'.

Market Basket Analysis: Shiny App

Market Prices Forecast (Daily Stock Trading) application (https://skipper.shinyapps.io/shiny_market_prices_forecast/ ) is in support of the stock trading simulation to be built. It uses ‘Quantmod’ R-package for getting price history and ‘Prophet’ package for prediction.
Select parametes in the menu above. The drop-down symbols is the list of 514 ETF securities. It may be changed by placing the new symbols column in ‘symbol.txt’ file in the working directory.

Use the Forecast tab to explore predictions for the chosen symbol.

Click the Financial Analysis tab to examine standard financial charts. To learn more about the project, click the About tab.

Application author: vladishat

Market Prices Forecast Shiny Web App

In this project a set of complex polynomial roots was found with the help of Newton's method. The close vicinity of different roots where plotted down by the correspondent colors which form Newton Fractals. The solution was programmed and calculated in Matlab.

Matlab: Newton Fractals

AI Chatbot on custom documents

High-Frequency Trading profitability

Sales Forecast (Shops & Stores Net)

Market Basket Analysis: Shiny App

Market Prices Forecast Shiny Web App

Matlab: Newton Fractals

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レビューを絞り込む：

5.0

$2,200.00 USD

192 2D B&W Matrix Images

Their expertise in math and understanding of the complex concepts involved was evident from the start. He delivered high-quality work that exceeded my expectations. I highly recommend him for any projects.

Ben M.

@benmccarty0

•

6か月前

5.0

$40.00 USD

D3graph Hierarchical Edge Bundling

A highly recommend and excellent freelancer who understands all requirements and is very professional.

JavaScript

Geospatial

Dthreejs

R Programming Language

Power BI

Faisal S.

@faisalsaihan

•

11か月前

4.8

€200.00 EUR

Optimisation model in python

Volodymyr is a very professional coder. He completed the project on time and he helped me framing the problem under different perspectives.

Python

Data Visualization

Data Analysis

Andrea G.

@Gila56045

•

1年前

5.0

$30.00 CAD

Project for Volodymyr S. -- 2

It was a really good experience to work with Volodymyr. He provided precise commentaries and the communication was clear.

Data Processing

Statistics

Machine Learning (ML)

R Programming Language

+1 もっと

Rafael D.

@rafaelalen

•

2年前

5.0

€76.51 EUR

Project for Volodymyr S. -- 2

Great work of Volo for a completely spontanous statistics exercise. He was quick to respond, asked the right questions and started straight away to deliver ahead of time for an additional feedback opportunity. [09 February, 2022] Prof Vlad did an outstanding job on a small but decisive and urgent analysis regarding crucial conflicts of interest statistic work. His input changed the way may people look at sponsorship. Exceptional effort over night. Thank you!

Data Processing

Statistics

Machine Learning (ML)

R Programming Language

+1 もっと

Hans S.

@hcstier

•

2年前

出版物

Sliding Mode Control of a solar power plant at weather fluctuated irradiance

INUDECO-18 https://inudeco.pro/en/

Matlab/Simulink model of Sliding Mode Control was built to optimize a solar panel performance at a fluctuating by weather irradiance. This dynamic model shows a high performance relative to the pre-calculated Maximum Power Point Tracker, which may significantly improve the outcome of a solar power plant. Keywords: INUDECO, solar power plant, Matlab, Simulink, Lyapunov function. https://drive.google.com/file/d/16P3qZoqDTXMoJIJqHE9tRfjBaXwg-K2G/view?usp=sharing

Mapping of X-ray contamination. A digital model

INUDECO-18 https://inudeco.pro/en/

This is a digital search and mapping of X-ray sources by means of a stationary set of sensors placed around the contaminated object. The problem was solved by the genetic algorithm. It was shown that in some cases of four and more detectors the X-ray sources may be mapped if their number does not exceed much the number of detectors. Keywords: Gamma-ray imaging, contamination, mapping, genetic algorithm. https://drive.google.com/file/d/1rGCbKTlDlMCLczj20vixVVSs-G6M9M2G/view?usp=sharing

Hidden revolution of human priorities: An analysis of biographical data from Wikipedia

Journal of Informetrics 10(1):124-131 · January 2016

A study of Wikipedia biographical pages is presented. It is shown that the dates of some historical cataclysms may be reproduced from peculiarities of lifespan changes over time. Categories were merged in just two classes. Being quite constant during almost the entire history, its ratio shows a sharp jump at the end of the 20th century mainly due to growth of Sport and Art groups over all others. Available at: http://www.science.smith.edu/dftwiki/images/7/7b/HiddenRevolutionHumanPriorities.pdf

Parsing Wikipedia XML dump

CodeProject, April 2016

Article presents pretty simple parser for "pages-articles" XML dump file, capable of extracting body texts of pages, titles of pages with categories a page belongs, and names of categories with their parent categories. Body texts are not cleaned from markup, in particular because it may contain important information. For each Wikipedia's article page, calculate number of references to it from other pages. Available at: http://www.codeproject.com/Articles/1094987/Parsing-Wikipedia-XML-dump

Hierarchy of categories and classifying Wikipedia articles using XML dump

CodeProject, July 2016

A hierarchical object is built from relationships between categories and their parents. It is used in a classifier, detecting if an article belongs to possibly far parent category. Available at: http://www.codeproject.com/Articles/1100006/Hierarchy-of-categories-and-classifying-Wikipedia