Category: 1. Caffe2

In the previous lesson, you learned to create a trivial network and learned how to execute it and examine its output. The process for creating complex networks is similar to the process described above. Caffe2 provides a huge set of operators for creating complex architectures. You are encouraged to examine the Caffe2 documentation for a… Continue reading Defining Complex Networks

In this lesson, you will learn to define a single layer neural network (NN) in Caffe2 and run it on a randomly generated dataset. We will write code to graphically depict the network architecture, print input, output, weights, and bias values. To understand this lesson, you must be familiar with neural network architectures, its terms and mathematics used in them. Network Architecture… Continue reading Creating Your Own Network

Before you learn to use a pre-trained model in your Python application, let us first verify that the models are installed on your machine and are accessible through the Python code. When you install Caffe2, the pre-trained models are copied in the installation folder. On the machine with Anaconda installation, these models are available in… Continue reading Verifying Access to Pre-Trained Models

Now, that you have got enough insights on the capabilities of Caffe2, it is time to experiment Caffe2 on your own. To use the pre-trained models or to develop your models in your own Python code, you must first install Caffe2 on your machine. On the installation page of Caffe2 site which is available at… Continue reading Installation

Last couple of years, Deep Learning has become a big trend in Machine Learning. It has been successfully applied to solve previously unsolvable problems in Vision, Speech Recognition and Natural Language Processing (NLP). There are many more domains in which Deep Learning is being applied and has shown its usefulness. Caffe (Convolutional Architecture for Fast Feature Embedding) is… Continue reading Introduction

In this tutorial, we will learn how to use a deep learning framework named Caffe2 (Convolutional Architecture for Fast Feature Embedding). Moreover, we will understand the difference between traditional machine learning and deep learning, what are the new features in Caffe2 as compared to Caffe and the installation instructions for Caffe2. Audience This tutorial is designed for… Continue reading Caffe2 Tutorial