Python for Computer Vision & Image Recognition - Deep Learning Convolutional Neural Network (CNN) - Keras & TensorFlow 2 4.4 (163 ratings) Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating
What you'll learn
- Get a solid understanding of Convolutional Neural Networks (CNN) and Deep Learning
- Build an end-to-end Image recognition project in Python
- Learn usage of Keras and Tensorflow libraries
- Use Artificial Neural Networks (ANN) to make predictions
- Use Pandas DataFrames to manipulate data and make statistical computations.
You're looking for a complete Convolutional Neural Network (CNN) course that teaches you everything you need to create a Image Recognition model in Python, right?
You've found the right Convolutional Neural Networks course!
After completing this course you will be able to:
- Identify the Image Recognition problems which can be solved using CNN Models.
- Create CNN models in Python using Keras and Tensorflow libraries and analyze their results.
- Confidently practice, discuss and understand Deep Learning concepts
- Have a clear understanding of Advanced Image Recognition models such as LeNet, GoogleNet, VGG16 etc.
How this course will help you?
A Verifiable Certificate of Completion is presented to all students who undertake this Convolutional Neural networks course.
If you are an Analyst or an ML scientist, or a student who wants to learn and apply Deep learning in Real world image recognition problems, this course will give you a solid base for that by teaching you some of the most advanced concepts of Deep Learning and their implementation in Python without getting too Mathematical.
0 Comments