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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1

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btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
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observer.observe(document.body, { childList: true, subtree: true });
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} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
mykolamelnykml (Mykola Melnyk) · GitHub
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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1

, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' mykolamelnykml (Mykola Melnyk) · GitHub
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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1

, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' mykolamelnykml (Mykola Melnyk) · GitHub
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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1

, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + ' mykolamelnykml (Mykola Melnyk) · GitHub
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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1

, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' mykolamelnykml (Mykola Melnyk) · GitHub
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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1

, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + ' mykolamelnykml (Mykola Melnyk) · GitHub
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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1

, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })(); mykolamelnykml (Mykola Melnyk) · GitHub
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mykolamelnykml/README.md

Greetings! 👋

My name is Mykola Melnyk, and I'm an ML expert with two decades of experience in the software development. I specialize in transforming complex business ideas into scalable, secure, and efficient AI-driven products. I have expert knowledge in various areas, enabling me to deliver cutting-edge, top-tier AI solutions that drive business growth and improve efficiency.

Key Areas of My Specialization:

📄 Natural Language Processing (NLP), Computer Vision (CV), and Optical Character Recognition (OCR): 5+ years of experience in document processing, understanding, and anonymization. Led the development of Spark OCR (Visual NLP) using technologies such as Python/Scala, PySpark, PyTorch, LLMs, LLama 3, Mini Gemini, LangChain, and Hugging Face Transformers.

Big Data Processing with Apache Spark: 7+ years of experience designing and optimizing large-scale data pipelines for high-performance processing. In-depth knowledge of Spark internals, Spark Structured Streaming, and creator/contributor to the open-source spark-pdf datasource project written in Scala, enhancing Spark’s capabilities.

🔒 Data De-identification & Anonymization: Expert in anonymizing sensitive data from text, images, PDFs, and DICOM files. I ensure privacy, security, and compliance with GDPR and HIPAA standards using NLP, OCR, and computer vision to remove or mask personal information, safeguarding data confidentiality.

🧬 Healthcare, Pharma, MedTech, BioTech Expertise: Over 5 years of experience in the healthcare and life sciences sectors, with a strong understanding of formats like DICOM, and expertise in delivering solutions specifically tailored to meet the unique needs of these industries.

TOP 5 Reasons to Work With Me

✅ End-to-End Expertise

✅ Complex Problem-Solving Ability

✅ Timely Delivery

✅ Transparent Communication

✅ Scalable Solutions

Professional Skills

🛠️ Programming Languages: Python, Scala

📊 Data Science & Machine Learning: NLP, Computer Vision, Large Language Models (LLMs), Optical Character Recognition (OCR), Model Productionalization, Deep Learning (PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Pandas, CLIP)

💡 LLMs and Related Tools: OpenAI GPT, Gemini, Llama 3, FLUX, Together.ai, Ollama, Hugging Face, Langchain, LlamaIndex, LangServe, LangGraph, QLORA, Streamlit, Gradio

Big Data & Distributed Systems: Big Data Processing, ETL, Stream Processing, Real-Time Aggregation, Apache Spark (PySpark, Spark ML, Spark Structured Streaming), Kinesis, Kafka, Databricks

🚀 Cloud Computing & Infrastructure: Amazon Web Services (AWS), Distributed Systems, CI/CD Pipelines, Docker, Jenkins, Graphite, Grafana, Elasticsearch, Kibana

⚙️ Databases: PostgreSQL, MongoDB, Redis, DynamoDB

💼 CRMs: Hubspot, ZohoCRM

Availability

Committed to long-term collaborations. Available full-time for your next project.

My Projects

Spark PDF DataSource

Spark Pdf


Source Code: https://github.com/StabRise/spark-pdf

Home page: https://stabrise.com/spark-pdf/

Quick Start Jupyter Notebook: PdfDataSource.ipynb


The project provides a custom data source for the Apache Spark that allows you to read PDF files into the Spark DataFrame.

Key features:

  • Read PDF documents to the Spark DataFrame
  • Support read PDF files lazy per page
  • Support big files, up to 10k pages
  • Support scanned PDF files (call OCR)
  • No need to install Tesseract OCR, it's included in the package

ScaleDP

ScaleDP


Source Code: https://github.com/StabRise/scaledp

Home page: https://stabrise.com/scaledp/

Quick Start Jupyter Notebook: https://github.com/StabRise/ScaleDP-Tutorials/blob/master/1.QuickStart.ipynb


ScaleDP is an Open-Source Library for processing documents using Apache Spark.

Key features:

  • Load PDF documents/Images
  • Extract text from PDF documents/Images
  • Extract images from PDF documents
  • OCR Images/PDF documents
  • Run NER on text extracted from PDF documents/Images
  • Visualize NER results

Github

Mykola's GitHub stats

Pinned Loading

  1. StabRise/spark-pdfStabRise/spark-pdfPublic

    PDF DataSource for Apache Spark, allow to read PDF files directly to the DataFrame and ocr it

    Scala 82 4

  2. StabRise/ScaleDPStabRise/ScaleDPPublic

    ScaleDP is an Open-Source extension of Apache Spark for Document Processing

    Python 19 1

  3. StabRise/n8n-nodes-pdf-redactionStabRise/n8n-nodes-pdf-redactionPublic

    n8n node for PDF Redaction - AI-powered sensitive data detection and redaction in pdf

    TypeScript 15 1