Caffe2, open-sourced by Facebook, is a simple, flexible framework for efficient deep learning. This course will teach you about Caffe2 and show you how to train your deep learning models. 

Why should one take this certification?

In this online course, you will learn the foundations of Deep Learning, understand how to build neural networks and develop an understanding of convolutional networks, RNNs, Adam, Dropout, BatchNorm and more. 

You’ll be working on various projects throughout this online course with a focus on how to train and manipulate a deep neural network effectively. All these will be practiced in Caffe2 using Python programming languages.

Who will benefit from taking this certification?

Job seekers looking for employment in various IT companies, PSUs or MNCs. Certification in Deep learning with Caffe framework benefits Data Science professionals, students and professionals across various Industries.

Companies that hire Vskills Deep Learning with Caffe2 Professionals

IT companies, MNCs, Consultancies hire Pytorch professionals for Data Science related opportunities. Companies employing Data Science include Capgemini, JP Morgan Chase, TCS, Wipro, Zensar, Accenture, Infor etc.

Deep Learning with Caffe2 Table of Contents

https://www.vskills.in/certification/deep-learning-with-caffe2-table-of-content


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TABLE OF CONTENTS


Module 1

SETTING UP CAFFE2

  • The Course Overview
  • Set Up Caffe2 on Linux
  • Understanding the Caffe2 Architecture
  • Transitioning from Machine Learning to Deep Learning
  • Running an Image Classifier Using Caffe2

IMPLEMENTING NEURAL NETWORKS AND DEEP LEARNING

  • Learn about Matrices Using Python – NumPy
  • Understanding and Implementing Logistic Regression and Neural Networks
  • Understanding and Implementing Deep Neural Networks

UNDERSTANDING CAFFE2

  • Caffe2 Introduction
  • Caffe2 Python Wrapper
  • Mathematical Operators in Caffe2
  • Network Creators and Assisters in Caffe2 – Part 1
  • Network Creators and Assisters in Caffe2 – Part 2
  • Network Creators and Assisters in Caffe2 – Part 3

UNDERSTANDING A CONVOLUTIONAL NEURAL NETWORK

  • How Machines Learn to See!
  • Introduction to Convolutional Neural Networks
  • Implement a Convolution Layer Using Caffe2
  • Pooling Layer and Dropout in Caffe2
  • Role of Activation Functions in Solving Non-Linear Optimization

IMPLEMENTING WEIGHT INITIALIZATION, OPTIMIZATION, AND REGULARIZATION

  • Machine Learning Strategy
  • How to Perform Data Selection, Preparation, and Processing
  • Regularization of Neural Networks
  • Optimizing Neural Networks
  • Optimization Algorithms

INTRODUCTION TO RECURRENT NEURAL NETWORK

  • Sequence Learning
  • Introduction to Recurrent Neural Networks
  • LSTMs – A Special Case of RNNs
  • Learning about Word Embeddings
  • Introduction to Augmented Recurrent Neural Networks


Module 2

GETTING STARTED WITH CAFFE2

  • The Course Overview
  • Why Deep Learning?
  • Machine Learning Categories
  • Why Caffe2?
  • Install and Set Up Caffe2
  • Build a Caffe2 Docker

BASIC ELEMENTS

  • Definition of a Computational Graph Through Examples
  • Introduce Workspace, Operators, and Nets
  • Working with Computational Graphs

BUILDING BLOCKS OF A TRAINING MODEL

  • Housing Price Prediction
  • Representing a Linear Regression Model in a Computational Graph
  • Training Procedure
  • Training a Linear Regression Model

SUPERVISED LEARNING AND TRANSFER LEARNING

  • Fashion Product Recognition Problem
  • What Is Supervised Learning?
  • What Is Transfer Learning?
  • Model Zoo in Caffe2
  • Fine-Tune a Model for Recognizing Fashion Products

SEQUENCE-TO-SEQUENCE LEARNING

  • Chatbot Customer Service
  • What Is Sequence-to-Sequence Learning?
  • What Are RNNs and LSTMs?
  • Training an RNN-Based Model to Write like Shakespeare

REINFORCEMENT LEARNING

  • Why Deep Reinforcement Learning?
  • What Is Deep Reinforcement Learning?
  • What Is Deep Q-Network?
  • Training a Deep Q- Network for Solving the Cart-Pole Problem

RUNNING AI IN YOUR HANDS

  • AI on Mobile Devices Using Face ID
  • Challenges in Running AI Models on Mobile Devices
  • SequeezeNet
  • Deploy SequeezeNet on a Mobile Device
“Exam scheduling to be done through user account” / “Exam once scheduled cannot be cancelled”
Date of Examination
05-Oct-2019
06-Oct-2019
19-Oct-2019
20-Oct-2019
02-Nov-2019
03-Nov-2019
16-Nov-2019
17-Nov-2019
07-Dec-2019
08-Dec-2019
21-Dec-2019
22-Dec-2019
Examination Time
01:00 PM - 02:00 PM
02:30 PM - 03:30 PM
04:00 PM - 05:00 PM
05:30 PM - 06:30 PM
10:00 AM - 11:00 AM
11:30 AM - 12:30 PM

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Tags: Caffe2, Deep learning, Deep learning with Caffe2, Data Science