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# Category: Machine Learning

### #014 TF Implementing LeNet-5 in TensorFlow 2.0

Highlights: In this post we will show how to implement a foundamental Convolutional Neural Network like $$LeNet-5$$ in TensorFlow. The LeNet-5 architecture was invented by Yann LeCun in 1998 and was the first Convolutional Neural Network. Tutorial Overview: Theory recapitulation Implementation in TensorFlow 1. Theory recapitulation The goal of $$LeNet-5$$ was to recognize handwritten digits. So, it takes as an input $$32\times32\times1$$ image. It is a grayscale image, thus the number of channels is $$1$$.…

### #012 TF Transfer Learning in TensorFlow 2.0

Highlights: In this post we are going to show how to build a computer vision model without building it from scratch. The idea behind transfer learning is that a neural network that has been trained on a large dataset can apply its knowledge to a dataset that it has never seen before. That is, why it’s called a transfer learning; we transfer the learning of an existing model to a new dataset. Tutorial Overview: Introduction Transfer…

### #011 TF How to improve the model performance with Data Augmentation?

Highlights: In this post we will show the benefits of data augmentation techniques as a way to improve performance of a model. This method will be very beneficial when we do not have enough data at our disposal. Tutorial Overview: Training without data augmentation What is data augmentation? Training with data augmentation Visualization 1. Training without data augmentation A familiar question is “why should we use data augmentation?”. So, let’s see the answer. In order…