You will get a house price predictor using AI
Project details
House Price Prediction - ML in Rust
A high-performance house price prediction system implemented in Rust, leveraging Rust's safety guarantees and blazing-fast performance for machine learning applications.
š Architecture
Architecture
š Features
Pure Rust Implementation: Built entirely in Rust for maximum performance and safety
Fast Data Processing: Using Polars for lightning-fast DataFrame operations
Production-Ready ML: Complete ML pipeline from data ingestion to API serving
AWS Integration: Model storage and versioning in S3
RESTful API: High-performance prediction serving
š Tech Stack
Language: Rust š¦
ML Processing: Polars for DataFrame operations
Model Storage: AWS S3
API Framework: Rust web framework
Development Tools:
cargo
rustc
rust-analyzer
VSCode/Cursor
A high-performance house price prediction system implemented in Rust, leveraging Rust's safety guarantees and blazing-fast performance for machine learning applications.
š Architecture
Architecture
š Features
Pure Rust Implementation: Built entirely in Rust for maximum performance and safety
Fast Data Processing: Using Polars for lightning-fast DataFrame operations
Production-Ready ML: Complete ML pipeline from data ingestion to API serving
AWS Integration: Model storage and versioning in S3
RESTful API: High-performance prediction serving
š Tech Stack
Language: Rust š¦
ML Processing: Polars for DataFrame operations
Model Storage: AWS S3
API Framework: Rust web framework
Development Tools:
cargo
rustc
rust-analyzer
VSCode/Cursor
AI Development Type
Deep Learning, Model Tuning, Recommendation SystemAI Tools
Amazon SageMaker, Apache MXNet, BigDL, Chainer, Deeplearning4j, Google AutoML, MLflow, OpenCV, PyTorch, TheanoAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$500
|
Standard
$750
|
Advanced
$1,000
|
|---|---|---|---|
| Delivery Time | 5 days | 7 days | 10 days |
Number of Revisions | 5 | 5 | 5 |
AI Model Integration | |||
Detailed Code Comments | |||
Knowledge Graph | - | ||
Model Documentation | |||
Ontology | - | ||
Source Code | |||
Taxonomy | - |
19 reviews
(18)
(0)
(0)
(0)
(1)
This project doesn't have any reviews.
RG
Rodney G.
Mar 30, 2026
Python Tutor for Hugging Face Models
Babatunde is an absolute professional. He did a spectacular job on my project - he showed up on time, he had accomplished pre-work, and perfectly delivered on the contract requirements. His technical expertise is excellent. He has a patient and solution-focused manner and is a joy to work with. I highly recommend him for your project.
RO
Ruth O.
Jan 17, 2026
AI Automation Engineer for RAG System Fix
Babatunde efficiently troubleshot our AI automation workflow and resolved the issue. He understood the problem fast and delivered exactly what we needed.
BY
Brian Y.
Jan 13, 2026
AI Researcher - LLM
SR
Ste R.
Jan 4, 2026
Full Local Conversational AI Agent ā LLM (Mistral) + RAG + Next.js
The work delivered did not comply with the agreed Statement of Work.
Essential contractual requirements were not met, and no independent and reproducible verification of compliance was provided, despite repeated requests. The delivery relied on artifacts and explanations rather than demonstrable and self-contained compliance with the specifications.
In addition, fundamental elements described in the scope were missing, with no usable or verifiable functionality.
As a result of these shortcomings, the contract ended in a dispute handled through Upwork mediation. I do not recommend this freelancer.
Essential contractual requirements were not met, and no independent and reproducible verification of compliance was provided, despite repeated requests. The delivery relied on artifacts and explanations rather than demonstrable and self-contained compliance with the specifications.
In addition, fundamental elements described in the scope were missing, with no usable or verifiable functionality.
As a result of these shortcomings, the contract ended in a dispute handled through Upwork mediation. I do not recommend this freelancer.
CA
Cindy A.
Aug 23, 2025
60 minute consultation
About Babatunde
AI Automation | Machine Learning | Ex Turing Engineer
100%
Job Success
Columbus, United StatesĀ - 7:38 am local time
No fluff, just real values.
With years of hands-on experience in developing, deploying, and optimizing AI solutions, I specialize in MLOps, Large Language Models (LLMs), and scalable AI infrastructure. My expertise spans end-to-end machine learning workflows, from model training to deployment, monitoring, and scaling in production.
I have successfully built and managed LLM-powered applications, ensuring efficiency, reliability, and scalability using modern MLOps practices. My work has driven innovation across healthcare, academia, and e-commerce, automating complex processes and enabling intelligent decision-making.
š„ Core Expertise
MLOps & AI Infrastructure:
ā Model Deployment: FastAPI, Flask, Docker, Kubernetes, AWS Lambda
ā Model Monitoring & Optimization: MLflow, Weights & Biases, Great Expectations, CometML
ā CI/CD for ML: GitHub Actions, DVC, Terraform, CloudFormation
ā Scalable Compute: AWS SageMaker, GCP Vertex AI, Azure Machine Learning
ā Vector Databases: Pinecone, ChromaDB, Weaviate, FAISS
ā Data Pipelines: Apache Kafka, Redpanda, Airflow, Prefect
LLMs & Generative AI:
ā LLM Fine-Tuning: BERT, GPT (OpenAI, Llama, Mistral, Claude), LoRA, QLoRA
ā Retrieval-Augmented Generation (RAG): LangChain, Haystack, Milvus
ā Prompt Engineering & Optimization
ā Open-Source LLMs: LlamaIndex, Hugging Face Transformers
ā AI Assistants: Chatbot Development, Multi-modal LLMs
Machine Learning & Deep Learning:
ā NLP: Named Entity Recognition (NER), Text Classification, Speech Recognition
ā Computer Vision: Object Detection (YOLO), Image Segmentation, OCR (Tesseract, PaddleOCR)
ā Supervised & Unsupervised Learning: XGBoost, Random Forest, SVM, KNN
ā Time-Series Forecasting & Anomaly Detection
Cloud & DevOps for AI:
ā AWS (S3, Lambda, SageMaker, Bedrock), GCP (Vertex AI, BigQuery)
ā Serverless AI Deployments & Microservices
ā SQL & NoSQL Databases: PostgreSQL, MySQL, MongoDB
š Why Work With Me?
ā Production-Ready AI ā I design and implement scalable ML pipelines that ensure smooth integration into real-world applications.
ā MLOps & AI Deployment ā From model versioning to automated retraining, I handle the full ML lifecycle.
ā LLM Optimization & Fine-Tuning ā I help businesses integrate custom AI assistants using the latest LLM research.
ā Robust & Scalable Code ā My solutions are efficient, well-documented, and optimized for long-term maintainability.
ā Transparent & Effective Communication ā I collaborate closely with clients, ensuring alignment at every stage of development.
Steps for completing your project
After purchasing the project, send requirements so Babatunde can start the project.
Delivery time starts when Babatunde receives requirements from you.
Babatunde works on your project following the steps below.
Revisions may occur after the delivery date.
Initial call
Project implementation and iteration.