Deep Learning on Google Cloud Platform
- Created By raju2006
- Last Updated December 27th, 2023
- Overview
- Prerequisites
- Audience
- Audience
- Curriculum
Description:
Master deep learning and harness the capabilities of Google Cloud Platform in this 'Deep Learning on GCP' course. Gain a profound understanding of deep learning's connection to machine learning and artificial intelligence. Explore the power of deep neural networks, utilizing Keras, TensorFlow, and GCP's AI Platform to apply deep learning to real-world datasets. Dive into Convolutional Neural Networks for image classification and leverage GCP services for creating, training, and deploying your AI solutions. Unleash the potential of deep learning with Google Cloud Platform.
Course Code/Duration:
BDT72 / 1 Day
Learning Objectives:
After this course, you will be able to:
- Understand Google Cloud Platform (GCP)
- Compare AI vs. ML vs. DL
- Understand How Machines Learn
- Understand Shallow and Deep Neural Networks
- Understand Convolutional Neural Networks
- Understand Deep Learning for Image recognition
- Use TensorFlow and Keras to Build Deep Learning Models
- Use AI Platform on GCP
- Use AI Platform Notebooks to Build and Train Deep
- Learning Models
- Use Cloud Shell on GCP
- Use Google’s Pre-built Machine Learning Models on GCP
- Understand the fundamental techniques through AI Demos and hands-on labs
- Python experience
- Basic understanding of Machine Learning
- This course is designed for Software Architects, Developers, Data Engineer, Data Analyst and Machine Learning Engineer.
- This course is designed for Software Architects, Developers, Data Engineer, Data Analyst and Machine Learning Engineer.
Course Outline:
- Course Introduction
- Compare AI vs ML vs DL
- Understanding how machines learn
- Structured vs. Unstructured data
Lab:
- Installing Anaconda and TensorFlow
- Introduction to neural networks
- The math behind neural networks
- Activation functions
- Vanishing gradient problem and ReLU
- Loss functions
- Gradient descent
- Back propagation
- Understanding the intuition behind neural networks
- Introducing Perceptrons
- Single Layer linear classifier
- Step Function
- Updating the weights
- Linear separability and XOR problem
- Hidden Layers: Intro to Deep Neural Networks
- Introducing Keras/TensorFlow
- TensorFlow intro
- What is Keras?
Lab:
- Using Keras to implement a neural network
- Understanding Images
- Images as visual data
Lab:
- Building a DNN model for image classification
- Deep Learning
- The architecture of deep learning
- The advantages of deep learning
- Convolutional Neural Networks
- Convolutions
- Size
- Stride
- Padding
- Pooling
- Fully-connected layer
- Dropout Layer
- Understanding Google Cloud Platform
Lab:
- Getting Started with GCP
- Using GCP for Deep Learning
- Project creation
- Cloud storage
- Introducing AI Platform
- AI Platform Notebooks
- TensorFlow
- AI Hub
Lab:
- Creating a TensorFlow model using AI Platform Notebooks
Lab:
- Building a Convolutional Neural Network
- Pre-built ML Models for Image Classification on GCP
- Understanding pre-built models
- Cloud Vision API
- GCP Deep Learning Project
Lab Project:
- Creating an Image Classifier with a CNN
- Next steps
Structured Activity/Exercises/Case Studies:
- Installing Anaconda and TensorFlow
- Using Keras to implement a neural network
- Building a DNN model for image classification
- Getting Started with GCP
- Creating a TensorFlow model using AI Platform
- Notebooks
- Building a Convolutional Neural Network
- Creating an Image Classifier with a CNN
Training material provided:
Yes (Digital format)
The curriculum is empty
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