You will get machine learning and data science in scikitlearn python
Project details
Linear Regression
Multiple Linear Regression
Logistic Regression
Clustering
XGBoost
Neural Networks
Decision Tree
Support Vector Machine
Random Forest Classifier
PCA
Multiple Linear Regression
Logistic Regression
Clustering
XGBoost
Neural Networks
Decision Tree
Support Vector Machine
Random Forest Classifier
PCA
What's included
| Service Tiers |
Starter
$50
|
Standard
$100
|
Advanced
$200
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 1 | 1 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 2 | 2 |
Number of Graphs/Charts | 1 | 3 | 5 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | |
Data Source Connectivity | - | - | - |
Source Code |
About Muhammad
Senior Fullstack AI Engineer | LLMs, RAG, Python, FastAPI, NextJS, GCP
Karachi, Pakistan - 8:05 am local time
I design and build end-to-end AI systems — from backend model pipelines to full-stack integration — that help businesses automate workflows, enhance data intelligence, and scale AI-driven solutions.
🔹 What I Do:
* LLM & Chatbot Development: Custom AI chatbots using LangChain, OpenAI GPT-4/Gemini, LLM fine-tuning, and multi-agent systems with memory and context management.
* RAG Pipelines: Build Retrieval-Augmented Generation architectures with pgvector/ChromaDB for semantic search, document Q&A, and enterprise knowledge bases.
* MLOps & Backend Systems: Design FastAPI or Flask-based APIs, containerize using Docker, and deploy on AWS/GCP with CI/CD automation (GitHub Actions).
* Data Science & Deep Learning: Develop models for document classification, computer vision, OCR, and NLP using TensorFlow, PyTorch, and HuggingFace Transformers.
* Frontend Integration: Build interactive ReactJS/NextJS UIs for AI platforms with features like chat history, multilingual support, Google Drive integration, and WhatsApp bot connectivity.
🔹 Key Achievements:
* Built a multi-tenant AI chatbot platform integrating LangChain, PostgreSQL (pgvector), and ReactJS — deployed on Google Cloud Platform.
* Created document slicing and classification pipelines using EfficientNet and GRU-LSTM models to process thousands of pages automatically.
* Developed an AI signature detection system using YOLOv5 + ResNet for verifying judge signatures in legal documents.
* Deployed and managed multiple RAG-based AI agents improving document search efficiency by 70%.
🔹 Tech Stack
Python, FastAPI, Flask, TensorFlow, PyTorch, LangChain, HuggingFace, OpenAI API, Google Gemini, PostgreSQL + pgvector, ChromaDB, Docker, GCP, AWS, ReactJS, NextJS, GitHub Actions, OCR, NLP, RAG, Multi-Agent Systems
🔹 Why Hire Me
✅ Proven track record of delivering production-grade AI systems
✅ Strong communication & client collaboration skills
✅ End-to-end ownership — from architecture to deployment
✅ Continuous learner and experimenter in emerging AI tools (ChatGPT, Copilots, LangGraph)
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Steps
*Analyze the given data *Preprocessing of data *Apply best fitted Algorithm by observing problem and data provided. *Visualize the results