Convolutional Neural Networks for Image Classification

Learn to build your own convolutional neural network for image recognition using Tensorflow 2.0, Keras, and the MNIST dataset.

What's Inside

This course includes downloadable project files.

Discover convolutional neural networks (CNNs) – the image recognition technology behind self-driving cars, facial recognition, fingerprint matching and more. Learn all about this popular type of neural network while building two models for identifying handwritten numbers – one using TensorFlow 2.0 (a highly popular machine learning library), and another using Keras (a modular library specifically for neural networks).

You will learn:

  • How image recognition works
  • Real-world applications of image recognition
  • What the MNIST dataset is, and how to access and use it
  • Building, training, and testing CNN models with Tensorflow
  • Building, training, and testing CNN models with Keras

…and more!

Requirements:

  • Basic knowledge of Python and Numpy
  • Familiarity with Machine Learning is necessary for this course.

Course Curriculum

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42004+ Students
19 Lectures
2+ Hours of Video
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Zenva

Trusted by over 1 million learners and developers, Zenva provides world-class training on in-demand programming skills covering game development, machine learning, virtual reality and full-stack web development.

Our e-learning platform Zenva Academy is the leading place to upskill, learn and gain key tech skills for the innovation economy. Our curriculum is organized about Mini-Degrees™ which cover a wide range of technical subjects and include video, project files and mentor support.

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