Convolutional Neural Networks in Python: CNN Computer Vision
Python for Computer Vision & Image Recognition - Deep Learning Convolutional Neural Network (CNN) - Keras & TensorFlow 2
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.
Description
The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Deep learning techniques and we have used our experience to include the practical aspects of data analysis in this course
What is covered in this course?
Part 1 (Section 2)- Python basics
Part 2 (Section 3-6) - ANN Theoretical Concepts
Part 3 (Section 7-11) - Creating ANN model in Python
Part 4 (Section 12) - CNN Theoretical Concepts
Part 5 (Section 13-14) - Creating CNN model in Python
Part 6 (Section 15-18) - End-to-End Image Recognition project in Python
By the end of this course, your confidence in creating a Convolutional Neural Network model in Python will soar. You'll have a thorough understanding of how to use CNN to create predictive models and solve image recognition problems.
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