Learn Python & OpenCV for Computer Vision Deep Learning, OCR
Build Powerful Computer Vision, Deep Learning, and OCR Solutions with Python, Numpy, Pandas, and OpenCV
What you will learn
Learn Python from the ground up and build your own computer vision and deep learning solutions.
Understand Python data types, operators, loops, functions, modules, and file handling, as well as best coding practices.
Master advanced Python concepts such as lambda functions, object-oriented programming, decorators, and generators.
Learn to use Python built-in libraries such as DateTime, Math, Random, Statistics, Sys, and OS.
Gain expertise in Numpy, Pandas, Matplotlib, and OpenPyXL for high-performance data manipulation and visualization.
Build a strong foundation in OpenCV to work with images and videos efficiently.
Use OpenCV to perform image thresholding, noise removal, cropping, rotation, annotation, and detection.
Apply OpenCV to live webcam and recorded video streams.
Develop Python solutions for web scraping, sending emails using Flask, and extracting text from PDF documents.
Build OpenCV solutions for template matching and object tracking in real time.
Why take this course?
Become a Computer Vision and Deep Learning Expert with Python and OpenCV
In this comprehensive course, you'll learn everything you need to know to master computer vision and deep learning with Python and OpenCV. You'll start with the basics of Python and OpenCV, and then gradually work your way up to more advanced topics, such as:
Image processing
Object detection and tracking
Scene classification
Image segmentation
Deep learning models for computer vision
You'll also learn how to build your own computer vision and deep learning applications using Python and OpenCV. By the end of the course, you'll be able to develop cutting-edge computer vision solutions to real-world problems.
What sets this course apart?
Comprehensive coverage of both Python and OpenCV
35+ supporting notebooks available for download
5 different varieties of projects to develop
Tutorials on setting up PyCharm and using Google Colab
Regular assessments to help you track your progress
Why learn Computer Vision and Deep Learning?
Computer vision and Deep Learning are two of the most rapidly growing fields in technology today. They are used in a wide variety of applications, including:
Self-driving cars
Medical imaging
Robotics
Security and surveillance
Social media and entertainment
If you're interested in a career in computer vision or deep learning, or if you simply want to learn about these exciting technologies, then this course is for you!
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