You will get a custom machine learning model for your business using Python
Rising Talent
Rising Talent
Project details
I specialize in building custom machine learning models using Python to help businesses turn data into real insights. Whether you're dealing with raw spreadsheets or complex datasets, I provide tailored ML solutions that are clean, accurate, and built for impact.
What sets this project apart is the end-to-end approach — from data cleaning and model training to evaluation and deployment-ready code. You’ll get a solution that’s not just technically sound but also aligned with your business goals.
Every model is crafted with professional tools like Scikit-learn, Pandas, NumPy, and includes full documentation, charts, and performance reports. I treat every client’s project as if it were my own product — reliable, optimized, and built to last.
Let’s transform your data into something powerful.
What sets this project apart is the end-to-end approach — from data cleaning and model training to evaluation and deployment-ready code. You’ll get a solution that’s not just technically sound but also aligned with your business goals.
Every model is crafted with professional tools like Scikit-learn, Pandas, NumPy, and includes full documentation, charts, and performance reports. I treat every client’s project as if it were my own product — reliable, optimized, and built to last.
Let’s transform your data into something powerful.
Machine Learning Tools
Azure Machine Learning, ChatGPT, GitHub Copilot, Google AutoML, Google Data Studio, Google Sheets, GPT-3, Microsoft Excel, Microsoft Power BI, NLTK, NumPy, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Scrapy, SQL, Stanford CoreNLP, TensorFlow, Tesseract OCR, Word2vecWhat's included
| Service Tiers |
Starter
$10
|
Standard
$30
|
Advanced
$150
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | Unlimited | Unlimited | 3 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 3 | 5 | 10 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$5 - $20Frequently asked questions
About Muhammad
AI/ML engineer
Islamabad, Pakistan - 4:05 am local time
Hi, I’m Muhammad Kashif, an AI Engineer specializing in the design and deployment of Autonomous Agentic Workflows and Advanced Computer Vision systems. Currently completing my B.S. in Artificial Intelligence at the National University of Computer and Emerging Sciences (FAST-NUCES), I operate at the intersection of cutting-edge research and commercial scalability.
The AI landscape has shifted from simple chatbots to Agentic Systems.AI that can reason, plan, use tools, and self-correct. I specialize in building these thinking systems. Whether you are looking to automate a multi-step business process, build a real-time Voice AI, or deploy industrial-grade Computer Vision on the edge, I provide the technical architecture to make it happen.
Deep Technical Expertise
1. Large Language Models (LLMs) & Agentic Orchestration
I design systems where LLMs act as the brain of a larger machine.
Frameworks: Mastery of LangChain, LangGraph, and CrewAI for building stateful, multi-agent teams that collaborate to solve complex tasks.
Advanced RAG: Implementation of Agentic Retrieval-Augmented Generation. This includes query expansion, hybrid search (Vector + Keyword), and Self-RAG systems that critique their own retrieved context to eliminate hallucinations.
Tool-Use: Enabling LLMs to interact with external APIs, SQL databases, and local file systems to perform real-world actions.
Model Proficiency: Implementation of GPT-4o, Claude 3.5 Sonnet, Llama 3.1 (Fine-tuned), and Gemini 1.5 Pro.
2. Computer Vision & Industrial AI
My experience with Vision Transformers (ViT) and real-time detection allows me to build eyes for your business.
Architectures: YOLOv8/v10 for object detection, UNet for semantic segmentation, and CNNs for high-accuracy medical classification.
Edge Deployment: Optimization of models for NVIDIA Jetson Nano and Coral TPU using TensorRT and ONNX, ensuring low-latency inference in industrial environments.
Medical AI: Developing pipelines for diagnostic-grade analysis of X-rays, MRIs, and clinical datasets.
3. Full-Stack AI Integration & Deployment
An AI model is only useful if it’s accessible. I build the entire bridge.
Backend: FastAPI (Asynchronous) for high-concurrency AI serving, Flask for rapid prototyping.
Frontend: Flutter for cross-platform mobile apps (iOS/Android) and modern Web interfaces.
Data Layer: Specialized in Vector Databases (ChromaDB, FAISS, Pinecone) for high-dimensional similarity search.
Voice & Audio: Real-time Speech-to-Speech integration using OpenAI Whisper and ElevenLabs with low-latency streaming.
Featured Case Studies & Impact
FabrIQ: AI-Powered Industrial Quality Control
As the lead developer for FabrIQ, I engineered a system to detect fabric defects in real-time. This involved:
Implementing Vision Transformers (ViT) to identify micro-tears and color inconsistencies.
Deploying the model on NVIDIA Jetson Nano hardware for on-site factory processing.
Reducing manual inspection time while increasing defect detection accuracy by leveraging custom-trained YOLOv8 models.
Rooh.AI: The First Pakistani Emotional AI Twin
As a Co-Founder, I spearheaded the development of a lifelike AI companion designed for empathy and support.
Context Management: Engineered a long-term memory system using a vector database to allow the AI to "remember" previous conversations.
Emotional NLP: Fine-tuned LLMs to detect emotional nuances in text and respond with appropriate sentiment.
Real-time Voice: Integrated ElevenLabs to provide a seamless, low-latency vocal response system.
Autonomous Lead-Gen & Market Intelligence Agents
For e-commerce clients, I built a CrewAI-based workforce:
Agent A (The Scout): Scrapes competitor websites and Amazon listings using Selenium/BeautifulSoup.
Agent B (The Analyst): Performs sentiment analysis on thousands of customer reviews to identify pain points.
Agent C (The Strategist): Generates a structured marketing report and emails it to the stakeholders—all with zero human intervention.
Why My Approach is Different
Strict Anti-Hallucination Protocols: I use Chain-of-Thought (CoT) prompting and deterministic output validation to ensure the AI only speaks facts.
Performance Optimization: I don't just call an API; I optimize for Tokens-Per-Second and cost-efficiency, ensuring your AI scales without breaking the bank.
Technical Toolbox
Languages: Python (Expert), Dart (Flutter), C++, SQL.
AI/ML: PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, OpenCV.
LLM Tools: LangChain, LangGraph, LlamaIndex, CrewAI, HuggingFace.
Database: PostgreSQL, MongoDB, ChromaDB,FAISS,Pinecone.
DevOps: Docker, FastAPI, AWS (S3/EC2), Git, Linux.
Let’s Build the Future Together.
I am looking for clients who want to push the boundaries of what AI can do. Whether it’s an MVP or a complex enterprise automation, I have the skills to deliver.
Drop a message to discuss how we can drive a measurable impact on your problem.
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.
Review Data & Understand Goals
I’ll analyze the dataset and your business goals to define the problem clearly.
Clean & Preprocess the Data
Clean & Preprocess the Data by finding Missing values, outliers, and irrelevant features will be cleaned and handled.