Table of Content
 


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


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