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Name: Michel Arents
Type: User
Name: Michel Arents
Type: User
Developed a dash application to visualize the live sentiment on a topic on twitter searched by user dynamically.
This generic SSIS script code loads any complex XML data into SQL Server Database. The table structure based on the XML structure is created dynamically and the data is loaded. There is an option of making this to work as Framework with Framework tables to store the File details and load the relationship between the tables in the XML File. The script loops through the XML files provided in the path and loads the data into the SQL Server database. All these values are configurable.
Listed Volatility and Variance Derivatives (Wiley Finance)
Machine learning Algorithms
Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.
This repository contains mini projects in machine learning with notebook files
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
A collection of machine learning examples and tutorials.
A repo for all the relevant code notebooks and datasets used in my Machine Learning tutorial videos on YouTube
An example mini data warehouse for python project stats, template for new projects
Python implementation for the market basket analysis.
Market basket analysis of retail and movie datasets using brute force and apriori algorithm
Market Basket Analysis using Apriori Algorithm on grocery data.
Market Basket Analysis What is it? Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. For example, if you are in an English pub and you buy a pint of beer and don't buy a bar meal, you are more likely to buy crisps (US. chips) at the same time than somebody who didn't buy beer.
Market Basket Analysis
You would have noticed alot of channel getting popular on YouTube just by uploading “Reddit to Text-To-Speech” YouTube Videos. So I decided to create a program that can automate the process of receiving, generating and uploading these videos to YouTube with as little intervention as possible. It took me one month to complete this project. I divided the project to 3 scripts. The idea was to minimize as much manual intervention as possible and automate all the trivial tasks. However the process cannot be 100% automated. For example comments with links in them cannot be kept as quality of the video will be comprised due to the TTS. Additionally while a comment might have a large number of votes it could potentially be offensive and not safe for a YouTube video and thus must be removed. The thumbnail, while partially generated, must be edited in order to create any kind of appeal to viewers to click on your video. The same goes for the title of the video which must be clickbait-y in order to receive any attention. I have attempted to streamline the manual process with the client program and it takes me approximately 30 minutes to create 6 videos (the max that can be uploaded within 24 hours with the YouTube Data API).
Artefact 3-day coding challenge in Python: 1 ETL Pipeline and some SQL queries
Index into MeiliSearch all given YouTube channels' video. Channels can be indexed under different index names.
Class mapping to combine classes with the same shapes
a machine learning dashboard that displays hyperparameter settings alongside visualizations, and logs the scientist's thoughts throughout the training process
Collection of notebooks I made to illustrate some machine learning concepts and models in this repo, most of the models in this repo are built once from scratch and once using built-in models from libraries like sklearn.
Machine Learning Tools
ETL, Python, SQL
Creating SSIS and SSAS project
MSc Dissertation on Credit Risk Modeling
A look at ETL features with SSIS
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.