You will get Custom AI Object Detection & Image Classification
Project details
You will get a custom AI Object Detection & Image Classification solution built around your specific dataset and business requirements. I will handle the complete machine learning pipeline, including dataset analysis, preprocessing, model development, training, validation, testing, optimization, and deployment-ready inference.
Depending on your project, I can build models to detect multiple objects in images or classify images into custom categories. The solution can use modern computer vision technologies such as Python, OpenCV, PyTorch, TensorFlow, and YOLO-based architectures.
You will receive a professionally structured project that includes trained model files, source code, an inference pipeline, evaluation results, and clear documentation. I focus on clean implementation, reliable predictions, reproducible training, and practical deployment rather than providing a basic demo model.
Whether you need an AI prototype, research project, business automation solution, or production-ready computer vision foundation, I will build the pipeline according to your requirements and dataset.
Depending on your project, I can build models to detect multiple objects in images or classify images into custom categories. The solution can use modern computer vision technologies such as Python, OpenCV, PyTorch, TensorFlow, and YOLO-based architectures.
You will receive a professionally structured project that includes trained model files, source code, an inference pipeline, evaluation results, and clear documentation. I focus on clean implementation, reliable predictions, reproducible training, and practical deployment rather than providing a basic demo model.
Whether you need an AI prototype, research project, business automation solution, or production-ready computer vision foundation, I will build the pipeline according to your requirements and dataset.
Machine Learning Tools
Amazon SageMaker, Azure Machine Learning, Keras, MLflow, NumPy, Open Neural Network Exchange, OpenCV, pandas, Python, PyTorch, scikit-learn, TensorFlow, Vertex AIWhat's included
| Service Tiers |
Starter
$70
|
Standard
$150
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 2 | 3 | 4 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 2 | 3 | 3 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
Frequently asked questions
About M Asad
Machine Learning Engineer | AI, LLM, RAG & Computer Vision
Lahore, Pakistan - 10:19 am local time
I’m a Machine Learning Engineer and Python Developer specializing in building practical AI and machine learning solutions from model development to API and application integration.
My core expertise includes:
• Machine Learning & Deep Learning
• Python, TensorFlow, Keras & Scikit-Learn
• LLM Applications, RAG & AI Agents
• LangChain & LangGraph
• Vector Databases — FAISS, Chroma & Qdrant
• NLP & AI Chatbots
• Computer Vision, OpenCV & YOLO
• FastAPI & REST APIs
• Predictive Analytics & Data Analysis
• React, Streamlit, Docker & Git/GitHub
I have professional experience designing and deploying ML services across NLP, computer vision, and predictive analytics. I’ve also built FastAPI-based REST APIs for ML models and integrated AI features into web applications.
My project experience includes an LLM-powered RAG assistant with agentic workflows, an agriculture AI assistant with English/Urdu chatbot support, a multimodal emotion-based recommendation system, a real-time fire detection system, and a YOLO-based object detection application.
I focus on building solutions that are practical, reliable, and ready to move beyond a basic prototype.
If you need help with an AI/ML model, RAG application, AI agent, computer vision system, predictive analytics solution, or FastAPI ML backend, I’d be happy to help.
Let’s turn your AI idea into a working solution.
Steps for completing your project
After purchasing the project, send requirements so M Asad can start the project.
Delivery time starts when M Asad receives requirements from you.
M Asad works on your project following the steps below.
Revisions may occur after the delivery date.
Dataset Analysis & Preparation
I will analyze your dataset, organize images and labels, identify data-quality issues, and prepare the data for model training.
Data Preprocessing & Annotation
I will preprocess and validate the images, prepare annotations, resize data, and create suitable training, validation, and test datasets.