Convolutional Neural Networks for Image Classification

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!

Frameworks and tools covered: Python 3.7, Anaconda 2019.10, Jupyter Notebook 6.0.1, NumPy 1.17, Matplotlib 3.1, Tensorflow 2.0, Keras 2.2.5

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