Data Science Project | Part 1 | Human Segmentation
Welcome to Part 1 of our Data Science Project series!
In this session we dive into the exciting field of human segmentation using deep learning techniques. This project is perfect for data science enthusiasts and professionals looking to gain hands-on experience with computer vision and image processing.
What You'll Learn:
Introduction to Human Segmentation: Understand the fundamentals of human segmentation, its applications, and its importance in fields like healthcare, security, and augmented reality.
Exploring the Dataset: A detailed look at the datasets used for human segmentation, including how to access and prepare them for analysis.
Data Preprocessing: Step-by-step guide on cleaning and preparing the data, including image resizing, normalization, and augmentation techniques to enhance model performance.
Understanding Segmentation Models: An introduction to popular segmentation models like U-Net, Mask R-CNN, and DeepLab, and how they work.
Building Your First Segmentation Model: A hands-on tutorial on setting up your development environment and building a basic segmentation model using a deep learning framework like TensorFlow or PyTorch.
Why Watch This Video?
This session is designed to provide a solid foundation for anyone interested in human segmentation. By the end of this session, you’ll be equipped with the knowledge to preprocess image data and build your first segmentation model.
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