I will develop custom object detection models using yolo, CNN, opencv

I can work on predictive analysis, recommendation systems, text classification, sentiment analysis, chatbots, object detection, clustering, exploratory data analysis, and more. I cover both research-based and real-world business problems.

I primarily use Python and R along with libraries like TensorFlow, PyTorch, Scikit-learn, Keras, OpenCV, NLTK, SpaCy, and Transformers for NLP, Deep Learning, Computer Vision, and Data Science tasks.

Yes, after training the model, I can deploy it into a website or app according to your requirements using Flask, FastAPI, or Streamlit.

Absolutely! No matter the complexity, I specialize in solving data science, NLP, computer vision, and deep learning problems with tailored solutions.

I follow best practices in data science and deep learning, use proper validation techniques, apply performance metrics, and ensure optimized, clean, and well-documented code for every project.

I can handle a wide range of computer vision and deep learning projects including object detection, image classification, image segmentation, face recognition, pose estimation, OCR, object tracking, and custom image processing pipelines. I work with YOLO, OpenCV, PyTorch, TensorFlow, and Python to d

I primarily use Python, OpenCV, YOLO (v5/v8/v11), PyTorch, TensorFlow, and Keras for computer vision and deep learning development. For data annotation and model training, I use tools like Roboflow and LabelImg. I can also integrate models into web apps or REST APIs depending on your project needs.

Yes, absolutely. I can train custom YOLO or deep learning object detection models on your dataset. This includes data annotation and labeling, model training, evaluation, and optimization. If you do not have a dataset, I can also assist with data collection and image processing to build one from scr

You will receive fully working Python code, the trained deep learning or machine learning model (with weights), a detailed README for setup and usage, performance metrics (accuracy, mAP, F1 score), and post-delivery support. All code is clean, commented, and ready for deployment or further developme

Delivery time depends on project complexity. A basic object detection or image classification model typically takes 3–5 days. More advanced deep learning systems involving custom model training, large datasets, or real-time image processing pipelines may take 7–14 days.