You will get End-to-end ML pipeline: data prep → training → containerized deployment
Project details
I build production-ready ML models that solve real business problems — start to finish. Send me your dataset (or grant access) and I’ll handle cleaning, labeling guidance, feature engineering, model selection, training, validation, hyperparameter tuning, and deployment with a scalable inference endpoint. I focus on measurable outcomes: higher accuracy, faster inference, and robust monitoring so models stay reliable in production.
What you get: data audit & cleaning script, EDA report, trained model (PyTorch/TensorFlow/sklearn), evaluation metrics & test set results, reproducible training notebook, containerized API (FastAPI + Docker), deployment guide (AWS/GCP/Azure or Docker image), and basic monitoring + retraining plan. I work with tabular, text (NLP), and image tasks (classification, detection). I’ll explain trade-offs (latency vs cost) and deliver production-ready code and documentation — no academic toys, just usable product work.
What you get: data audit & cleaning script, EDA report, trained model (PyTorch/TensorFlow/sklearn), evaluation metrics & test set results, reproducible training notebook, containerized API (FastAPI + Docker), deployment guide (AWS/GCP/Azure or Docker image), and basic monitoring + retraining plan. I work with tabular, text (NLP), and image tasks (classification, detection). I’ll explain trade-offs (latency vs cost) and deliver production-ready code and documentation — no academic toys, just usable product work.
Machine Learning Tools
Azure Machine Learning, BERT, Databricks MLflow, deeplearn.js, fastText, GoLearn, Google AutoML, MLflow, NLTK, NumPy, NVIDIA AI Platform, OpenCV, pandas, PyMC, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Sonnet, SQL, Stanford CoreNLP, TensorFlow, Tesseract OCR, Vertex AIWhat's included
| Service Tiers |
Starter
$150
|
Standard
$650
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 10 days | 21 days | 28 days |
Number of Revisions | 0 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Model Validation/Testing | - | ||
Model Documentation | - | - | |
Data Source Connectivity | - | ||
Source Code |
About Abhi
AI/ML Engineer
Greater Noida, India - 8:41 am local time
I specialize in full-stack development + AI automation, meaning I handle everything — backend architecture, APIs, databases, frontend dashboards, AI model integration, and deployment — without handoffs or guesswork.
What I Build
AI-powered SaaS platforms (MVP → production)
Trading, betting & crypto automation bots
Data scraping & large-scale automation systems
AI agents, chatbots, image & voice-based systems
Secure backend APIs & admin dashboards
End-to-end deployed systems (cloud / VPS)
Tech Stack
Backend: Node.js, Python, TypeScript
Frontend: React, Next.js
AI/ML: GPT/OpenAI, custom models, image & voice models
Automation: Bots, scrapers, workflows
Database & Infra: SQL/NoSQL, cloud deployment
Why Clients Hire Me
I build complete systems, not fragments
I understand automation, scale, and performance
I think in business logic, not just code
One developer — no coordination overhead
If you need a reliable engineer who can design, build, automate, and deploy complex systems, I’m the right fit.
Steps for completing your project
After purchasing the project, send requirements so Abhi can start the project.
Delivery time starts when Abhi receives requirements from you.
Abhi works on your project following the steps below.
Revisions may occur after the delivery date.
Create a High Level Architecture for the project.