You will get machine learning pipeline with Python, TensorFlow, and AWS
Project details
This project delivers a robust, scalable machine learning pipeline built with Python, TensorFlow, and AWS, engineered for high-performance predictive modeling, data processing, and automation. Powered by Python and TensorFlow, the pipeline supports advanced ML tasks like classification, regression, or anomaly detection, leveraging TensorFlow’s deep learning capabilities for accurate, optimized models. AWS services, such as S3 for storage, SageMaker for model training, and Lambda for serverless execution, ensure seamless scalability and real-time processing of large datasets, from CSVs to streaming data. The pipeline integrates with APIs or existing systems, enabling efficient data ingestion and output delivery for users like data scientists or business analysts. Designed with a secure, compliant architecture, it adheres to regulations like GDPR or CCPA. Development includes discovery, data preprocessing, model development, AWS integration, rigorous testing, and deployment with user training.
Machine Learning Tools
Accord.NET Framework, Apache Mahout, Apache Spark MLlib, BERT, Chainer, Databricks Platform, Deeplearning4j, GitHub Copilot, Google Data Studio, GPT-3, Keras, KNIME, MATLAB, Microsoft Excel, Microsoft Power BI, NLTK, Open Neural Network Exchange, pandas, Python, Python Scikit-Learn, PyTorch, R, RapidMiner, SASWhat's included
| Service Tiers |
Starter
$100
|
Standard
$5,000
|
Advanced
$10,000
|
|---|---|---|---|
| Delivery Time | 1 day | 5 days | 10 days |
Number of Revisions | 0 | 1 | 2 |
Model Validation/Testing | - | ||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code | - | - |
About Vadym
Expert Conversational AI | Agentic AI Architect | Multi-Agent Systems
100%
Job Success
San Francisco, United States - 7:42 pm local time
I don't build simple chatbots. I design AI systems that think, plan, execute multi-step tasks, and self-correct - autonomously.
What I specialize in:
- Agentic AI Architecture: Designing autonomous agent systems using LangChain, LangGraph, CrewAI, AutoGPT, Clawdbot, Moltbot, and OpenClaw. My agents handle orchestration, reasoning, tool use, memory management, and self-healing — achieving 99.7% task completion rates in production.
- Conversational AI Engineering: Building enterprise-scale dialogue systems with advanced NLU/NLG, multi-turn context management, persona modeling, and emotional intelligence layers. My systems handle 10M+ monthly interactions with sub-200ms latency.
- Multi-Agent Systems: Architecting collaborative agent ecosystems where specialized AI agents coordinate, negotiate, and solve complex problems no single agent can — across finance, healthcare, retail, and logistics.
- RAG & LLM Integration: Production RAG pipelines with Pinecone, Weaviate, Chroma, hybrid search, and re-ranking. Advanced prompt engineering (chain-of-thought, tree-of-thought) that improves accuracy by 35–50% over baseline.
- Full-Stack AI Infrastructure: GPT-4/4o, Claude, LLaMA, Mistral, Gemini | Rasa, Dialogflow, Amazon Lex | AWS, Azure, GCP | Python, TypeScript, FastAPI, Kafka, Kubernetes
Results I've delivered:
→ Cut operational costs by up to 40% through intelligent agentic automation
→ Improved customer resolution rates by 60%+ with advanced conversational AI
→ Processed hundreds of millions of interactions across enterprise deployments
→ Maintained a perfect client satisfaction record across 12+ years
What sets me apart:
Most AI engineers know one piece of the puzzle. I operate across the full spectrum - from NLU and dialogue management to autonomous agent orchestration and multi-agent coordination. This convergent depth is rare, and it's why my systems perform at a level most teams can't replicate.
Whether you need a production agentic AI system, an intelligent conversational platform, a RAG-powered knowledge assistant, or a full multi-agent architecture - I'll design it, build it, and make sure it delivers.
Let's talk about what you're building.
Steps for completing your project
After purchasing the project, send requirements so Vadym can start the project.
Delivery time starts when Vadym receives requirements from you.
Vadym works on your project following the steps below.
Revisions may occur after the delivery date.
Define & Design
Build & Integrate