You will get AI-Powered Document Understanding Solution
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Top Rated
Project details
Anadea offers an advanced machine learning-based document understanding solution that extracts structured data from unstructured documents like invoices, contracts, and forms — accurately, at scale.
What’s Included (Deliverables)
• NER model trained to extract key fields (e.g. invoice number, date, amount, vendor name)
• Packaged ML pipeline for processing PDFs, images, or scanned documents
• Validation and accuracy report on your dataset
• Demo interface for testing document uploads and extractions
• Export-ready structured output (JSON, CSV or as needed)
• Documentation for developers and users
• Deployment-ready solution: delivered via API or containern
What’s Included (Deliverables)
• NER model trained to extract key fields (e.g. invoice number, date, amount, vendor name)
• Packaged ML pipeline for processing PDFs, images, or scanned documents
• Validation and accuracy report on your dataset
• Demo interface for testing document uploads and extractions
• Export-ready structured output (JSON, CSV or as needed)
• Documentation for developers and users
• Deployment-ready solution: delivered via API or containern
Machine Learning Tools
Apache Spark, Azure Machine Learning, ChatGPT, GitHub Copilot, GPT-3, Keras, Kubeflow, Minitab, MLflow, NLTK, NumPy, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, pandas, PyMC, Python Scikit-Learn, PyTorch, scikit-learn, Shogun Toolbox, TensorFlow, Tesseract OCR, Vertex AI, Weka, XGBoostWhat's included $25,000
These options are included with the project scope.
$25,000
- Delivery Time 60 days
- Number of Revisions 0
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
About Andriy
Machine Learning Engineer
100%
Job Success
Novoyavorivs'k, Ukraine - 11:59 am local time
Programming languages:
Python, R, SQL
Data Manipulation & Wrangling:
Pandas, Numpy, Scipy, Statsmodels, Scikit-learn, JSON, SQLite, BeautifulSoup
Data Visualization and Interpretation:
Matplotlib, Seaborn, Plotly, PIL, Bokeh, ggplot
Classic Machine Learning:
Scikit-learn, LGBM, XGBoost, CatBoost, Optuna, H2O, Imblearn
Recommendation Systems:
LightFM, Implicit, recommenders, Cornac
Computer Vision(classification/segmentation/detection/tracking):
Pytorch, PIL, OpenCV, YOLO, STEGO
Image Generation(GenAI):
StableDiffusion, Dreambooth
Large Language Models(LLM):
Alpaca, LLaMA, MPT-7B
NLP:
HuggingFace, NLTK, Spacy, GenSim, TextBlob, polyglot, CoreNLP, Pattern
Cloud:
AWS S3, AWS EC2, AWS SNS, AWS RDS, AWS Auto Scaling, AWS Lambda, AWS CloudWatch, RunPod
Deployment:
Streamlit, Fastapi, Docker, Flask
Tools:
Jira, Trello, Git, BitBucket, GitLab, VSCode, Jupyter Notebook, DockerHub, DigitalOcean
Our Key Stats & Achievements
🏆 194+ successful projects completed on Upwork with global clients
💲 $5M+ earned on Upwork through high-impact full-stack and AI solutions
⏱ 55,121+ hours billed, proving long-term client trust and engagement
💼 600+ total projects delivered since 2000 across AI, web, and mobile
📚 100% of developers hold engineering degrees, ensuring expert-level technical depth
👩💻 Advanced AI team includes Kaggle competition masters and top ML researchers
📊 99%+ job success rate, reflecting top-tier performance and consistency
🚀 25+ AI-driven apps deployed in FinTech, EdTech, and HealthTech
🧠 30+ machine learning models built and optimized for live environments
🌎 20+ industries served, from startups to Fortune 500 clients
🧱 Founded in 2000, bringing 24+ years of experience in software innovation
🛠 40+ React + Python full-stack solutions developed for scalable applications
⚡ High-load systems deployed to serve thousands of concurrent users
📈 Client ROI increased by up to 70% in AI automation projects
💬 Featured in Forbes, MBN Magazine, and Helsinki Times for client success stories
If you are seeking a dependable, innovative, and top-notch ML expert, you've arrived at the correct destination - I am enthusiastic about becoming your trusted long-term collaborator. Let us embark on this journey together and begin our collaboration!
Keywords for me:
Python | R | SQL | Machine Learning | Data Science | Deep Learning | Artificial Intelligence | MLOps | Generative AI | GenAI | LLM | Large Language Models | LangChain | RAG | Vector Database | Pinecone | FAISS | ChromaDB | Weaviate | Milvus | Haystack | HuggingFace Transformers | OpenAI API | GPT-4 | Claude | Vertex AI | Bedrock | Agentic AI | AutoGPT | BabyAGI | CrewAI | LangGraph | AI Agents | Memory-augmented Agents | Prompt Engineering | Retrieval-Augmented Generation | Conversational AI | Chatbot Development | Voicebot | Whisper ASR | Audio AI | Stable Diffusion | Dreambooth | DALL·E | Midjourney | Computer Vision | YOLO | OpenCV | Image Segmentation | Image Classification | Object Detection | Pytorch | TensorFlow | Keras | ONNX | CVAT | Label Studio | NLP | Text Classification | Named Entity Recognition | Sentiment Analysis | Topic Modeling | Summarization | Translation | HuggingFace | Spacy | NLTK | Gensim | OpenAI Whisper | LlamaIndex | Alpaca | LLaMA | Mistral | MPT | MosaicML | Fine-Tuning | Few-shot Learning | Zero-shot Learning | Reinforcement Learning | Recommendation System | LightFM | Implicit | Recommenders | Time Series Forecasting | Anomaly Detection | Clustering | XGBoost | LightGBM | CatBoost | Optuna | H2O.ai | Pandas | Numpy | Scipy | Scikit-learn | Statsmodels | Data Wrangling | Feature Engineering | Model Evaluation | Explainable AI | SHAP | LIME | Data Visualization | Plotly | Matplotlib | Seaborn | Bokeh | Streamlit | Gradio | FastAPI | Flask | Docker | Kubernetes | MLflow | DVC | Git | GitHub Actions | GitLab CI/CD | Jupyter Notebook | Google Colab | AWS SageMaker | AWS Lambda | AWS EC2 | AWS S3 | AWS RDS | Google Cloud AI Platform | Vertex AI | Azure ML | RunPod | DigitalOcean | API Integration | SaaS AI | Full-Stack AI | End-to-End ML Projects | ChatGPT Integration | Automation | AI Copilot Development | Data Pipelines | ETL | Apache Airflow | Kafka | Redis | MongoDB | PostgreSQL | SQLite | NoSQL | SQLAlchemy
Steps for completing your project
After purchasing the project, send requirements so Andriy can start the project.
Delivery time starts when Andriy receives requirements from you.
Andriy works on your project following the steps below.
Revisions may occur after the delivery date.
Data collection & annotation
Model training & evaluation