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100% OFF Data Science ★ 4.0 200 students 1 hour

Computer Vision with Python

Mastering Computer Vision with the Python programming Language

Description


In this class you will learn how to build Computer Vision algorithms for Image classification and Object detection using the Python Programming Language. We will first go through Neural Networks Basics: what are Neural networks , what is the theory behind neural networks , then we will talk about binary classifiers like an SVM for classifying the MNIST datasets, Students will learn how to classify the hand written digits of the MNIST dataset into multiple classes. We will discuss the different types of edge detectors to detect edges in images. After this we will discuss convolutionnal neural networks: how are they built, what are the most common and efficient CNN architectures and how do you implement them in Python. The topic of Object detection and Exhaustive search will also be dealt with. The last part of the class will be an example application of building and training a custom built Convolutionnal neural Network on the cloud to classify images from an open source dataset. All the steps from getting data, reading the data , building the network and training the network on the cloud will be carefully explained so that the student has a working example to be able to reuse for its own purpose.

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Total Students200
Duration1 hour
LanguageEnglish (US)
Original Price₹799
Sale Price 0
Number of lectures20
Number of quizzes0
Total Reviews4
Global Rating4
Instructor NameLucas Mayrhofer

Course Insights (for Students)

Actionable, non-generic pointers before you enroll

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Student Satisfaction

78% positive recent sentiment

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Momentum

Steady interest

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Time & Value

  • Est. time: 1 hour
  • Practical value: 6/10

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Roadmap Fit

  • Beginner → Beginner → Advanced

Key Takeaways for Learners

  • Hands-on practice
  • Real-world examples
  • Project-based learning

Course Review Summary

Signals distilled from the latest Udemy reviews

What learners praise

Clear explanations and helpful examples.

Watch-outs

  • Error
  • Too fast
  • Too slow

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Difficulty

Beginner

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Best suited for

New learners starting from zero

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