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Tag: Python

#007 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – Spirals dataset

Highlights: In this post we will see how we can classify a spirals dataset with a shallow neural network implemented in TensorFlow 2.0. Tutorial Overview: Imports and Dataset preparation Building a Neural Network Visualization 1. Dataset: import and preparation Let’s start by importing libraries that we will need in our code. Last time we were using a function from sklearn to create a dataset. Now we are going to make our dataset from scratch. First,…
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#006 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – Moons dataset

In this post we will learn how to make a classification of Moons dataset with a shallow Neural network. The Neural Net we will implemented in TensorFlow 2.0 using Keras API. With the following code we are going to import all libraries that we will need. First, we will generate a random dataset, then we will split it into train and test set. We will also print dimensions of these datasets. With the following code…
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#005 TF 2.0 An implementation of a Shallow Neural Network with tf.keras – Circles dataset

Highlights: In previous post we have talked about TensorFlow Wrappers and there we concluded that tf.keras is the most convenient way to build neural networks. Now we are going to implement one very simple network using this high-level API. Tutorial Overview: Imports and Dataset preparation Building a Neural Network Visualization 1. Imports and Dataset preparation Let’s start with basic imports. Don’t worry if some things are not familiar with all of these libraries, we will…
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#011 TF YOLO V3 Object Detection in TensorFlow 2.0

YOU ONLY LOOK ONCE Highlights: Prior to Yolo majority of approaches for object detection tried to adapt the classifiers for the purpose of detection. In YOLO, an object detection has been framed as a regression problem to spatially separated bounding boxes and associated class probabilities. In this post we will learn about the YOLO Object Detection system, and how to implement such a system in TensorFlow 2.0. About Yolo:Our unified architecture is extremely fast. Our…
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CamCal 009 Stereo Geometry – Epipolar lines and Essential Matrix

Highlights: In this post we continue our talk about stereo geometry. We will show the relation between two calibrated cameras. The goal is to transform geometry into algebra, so then the computer can understand it. Tutorial Overview: This post covers the following topics: Intro Stereo Correspondence Stereo Geometry Cross Product 1 From Geometry to Algebra Cross Product 2 Essential Matrix 1. Intro Before we start, we have to remind ourself some things. So first thing…
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