Keras to Kubernetes The Journey of a Machine Learning Model to Production 1st Edition by Dattaraj Rao 1119564832 9781119564836

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ISBN 10: 1119564832

ISBN 13: 9781119564836

Author: Dattaraj Rao

We have seen an exponential growth in the use of Artificial Intelligence (AI) over last few years. AI is becoming the new electricity and is touching every industry from retail to manufacturing to healthcare to entertainment. Within AI, we?re seeing a particular growth in Machine Learning (ML) and Deep Learning (DL) applications. ML is all about learning relationships from labeled (Supervised) or unlabeled data (Unsupervised). DL has many layers of learning and can extract patterns from unstructured data like images, video, audio, etc.

Keras to Kubernetes: The Journey of a Machine Learning Model to Production takes you through real-world examples of building DL models in Keras for recognizing product logos in images and extracting sentiment from text. You will then take that trained model and package it as a web application container before learning how to deploy this model at scale on a Kubernetes cluster. You will understand the different practical steps involved in real-world ML implementations which go beyond the algorithms.

Keras to Kubernetes The Journey of a Machine Learning Model to Production 1st Table of contents:

CHAPTER 1: Big Data and Artificial Intelligence

Data Is the New Oil and AI Is the New Electricity
Applications of Artificial Intelligence
Summary

CHAPTER 2: Machine Learning

Finding Patterns in Data
The Awesome Machine Learning Community
Types of Machine Learning Techniques
Solving a Simple Problem
Analyzing a Bigger Dataset
Comparison of Classification Methods
Bias vs. Variance: Underfitting vs. Overfitting
Reinforcement Learning
Summary

CHAPTER 3: Handling Unstructured Data

Structured vs. Unstructured Data
Making Sense of Images
Dealing with Videos
Handling Textual Data
Listening to Sound
Summary

CHAPTER 4: Deep Learning Using Keras

Handling Unstructured Data
Welcome to TensorFlow and Keras
Bias vs. Variance: Underfitting vs. Overfitting
Summary

CHAPTER 5: Advanced Deep Learning

The Rise of Deep Learning Models
New Kinds of Network Layers
Building a Deep Network for Classifying Fashion Images
CNN Architectures and Hyper‐Parameters
Making Predictions Using a Pretrained VGG Model
Data Augmentation and Transfer Learning
A Real Classification Problem: Pepsi vs. Coke
Recurrent Neural Networks
Summary

CHAPTER 6: Cutting‐Edge Deep Learning Projects

Neural Style Transfer
Generating Images Using AI
Credit Card Fraud Detection with Autoencoders
Summary

CHAPTER 7: AI in the Modern Software World

A Quick Look at Modern Software Needs
How AI Fits into Modern Software Development
Simple to Fancy Web Applications
The Rise of Cloud Computing
Containers and CaaS
Kubernetes: A CaaS Solution for Infrastructure Concerns
Summary

CHAPTER 8: Deploying AI Models as Microservices

Building a Simple Microservice with Docker and Kubernetes
Adding AI Smarts to Your App
Packaging the App as a Container
Pushing a Docker Image to a Repository
Deploying the App on Kubernetes as a Microservice
Summary

CHAPTER 9: Machine Learning Development Lifecycle

Machine Learning Model Lifecycle
Deployment on Edge Devices
Summary

CHAPTER 10: A Platform for Machine Learning

Machine Learning Platform Concerns
Putting the ML Platform Together
Summary

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Tags: Dattaraj Rao, Kubernetes, Journey, Machine, Keras