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anomaliesdetection-with-timeseriesanalysis

This is an experimental of anomalies detection by applying different approach to the problem. PCA component regularization method, K-Mean Clustering, SVM and Gausian Distribution models has been used to detect anomalies on time series data.

autoencoder_outliers

Find outliers in data with AutoEncoders

automatic-data-parsing-structuring-grouping-writer

This Python code read CSV file and automatically recongizes real estate properties, finds specific cells at Excel file where specific values should be written, make all Excel formating and building all neccesary formulas only by one click! Half day work done just in half a minute.

aws-cicd-pipeline

Experimenting on CICD and Terraform

booking.com-data-scrapper-selenium

This Python made web scrapper gather all possible data (features) of properties in chosen area in ant place of the world. Due to dynamic content that is delivered by JavaScript scripts, Selenium was choosen as the best Python libary to gather such data. © Vytautas Bielinskas 2017

booking.com-price-scrapper-selenium

This Python algorithm will gather data of prices for 365 next days for specific chosen hotel on Booking.com. There can be some bug for testing on different properties but for our target property is worked perfectly. (© Vytautas Bielinskas)

corr_matrix_sns_experiment

Showing a normal and improved way to build a heatmap with Seaborn

cousera-advanced-data-science-with-ibm-specialization

crime-map

Interactive Crime Map (based on Flask)

cython_vs_python

Compare Cython and Python native functions - very simple example

data-cleaning-with-ecdf

The main idea is ECDF helps us to detect data outliers, in other words - data noise that must be removed from original (raw) dataset. This called as an iteration. After each iteration data get more and more clear. This is one of most technique for Data Preproccessing (Data Cleaning) based on Statistics mostly. For making code more structured I divided the whole algorithm to separate sections. Important procedures (ECDF, calculate percentiles, plot the data) are defined as Python definition with input arguments.

deep-learning---recognize-infected-cells-by-malaria--adam--sigmoid-

The project contain folders for labeled infected and non-infected cells by malaria. The code define an 4 layers ANN that learning to recognize infected cells by a given shuffled examples from working directory and provide a learning curve as output. For optimization Adam and MiniBatch methods have been applied (Tensorflow).

denmark-metro-and-real-estate-analysis--eda-

This project is quite big and this resposity is only the small part of whole project. This resp. correspond to geostatial analysis combining real estate listing and Metro station data. The task of the project: identify the impact of new new built metro stations to changes in prices of 500 m around real estate properties.

deploy-ml-mlflow-aws

Deploying Models to Production with Mlflow and AWS Sagemaker

deploy_kubernetes_aws_ec2

This manual explain how to setup AWS EC2 instance and set-up a Kubernetes Cluster inside

docker-container

Preparing for badge

docker-to-aws-ecr

Test

dvc_project

For Youtube tutorial - Data Science Garage

ensemble-learning-testing-classifiers

Testing and Exploration of Ensemble Learning with poor dataset (66 obs). Results are provided at the end of the Notebook.

farmer

feature-engineering-manually-

This is attempt to perform Feature Engineering to Real Estate Dataset in order to extract the most significant features for Machine Learning (ML) Part. © Vytautas Bielinskas

flask-api-template

This is the clear API grounded on Flask background with few simple outputs. Easy to transform to any real world application.

g-website

Personal Profile Website

github-action-to-ecr

Repo demonstrating how to create an AWS ECR Image with Github Action

groupingimages

identify-users-geo-data

This project analysis user data (how they uses the app), identify their home and work loacation based on parsed geo data. K-mean clustering applied to determine number of possible locations for home and work.

imagesimilarityapp

This app. perform image similarity calculations for a given image.

immobilescout24-scraping-by-submarket-and-plot-it

This web scrapper gather all possible data (features) from immobilescout24.de for each selected district (let's call is as 'submarket') and save it to separate Excel file with unique timestamp. There are also data visualzation part in the code that can be switchen on/off. © Vytautas Bielinskas

immobilienscout24.de-scrapper

This Python based Web Scrapper gather all possible values of real estate properties features from www.immobilienscout24.de that is the biggest Real Estate web listing page in Germany Real Estate market. This scrapper gather data for rental properties. Suprising is that only BeautifulSoup was enough to build this scrapper. And magical thing - Geocoding by connection to Google Maps API is implementing inside this Python code! © Vytautas Bielinskas 2017-2018

k-nn-machine-learning-neighbors

This K-NN Machine Learning algorithm take data from external source and testing Train and Test sets to get values of accuracies delivered by algorithm based on different number of n_neighbors (hyperparameter of KNeighborsClassifier). © Vytautas Bielinskas 2018