Beginning Machine Learning with AWS

Beginning Machine Learning with AWS, available at $29.99, has an average rating of 3.35, with 36 lectures, 6 quizzes, based on 22 reviews, and has 122 subscribers.

You will learn about Get up and running with machine learning on the AWS platform Analyze unstructured text using AI and Amazon Comprehend Create a chatbot and interact with it using speech and text input Retrieve external data via your chatbot Develop a natural language interface Apply AI to images and videos with Amazon Rekognition This course is ideal for individuals who are Machine Learning with AWS is ideal for data scientists, programmers, and machine learning enthusiasts, who want to learn about the artificial intelligence and machine learning capabilities of the Amazon Web Services. It is particularly useful for Machine Learning with AWS is ideal for data scientists, programmers, and machine learning enthusiasts, who want to learn about the artificial intelligence and machine learning capabilities of the Amazon Web Services.

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Summary

Title: Beginning Machine Learning with AWS

Price: $29.99

Average Rating: 3.35

Number of Lectures: 36

Number of Quizzes: 6

Number of Published Lectures: 36

Number of Published Quizzes: 6

Number of Curriculum Items: 42

Number of Published Curriculum Objects: 42

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Get up and running with machine learning on the AWS platform

Analyze unstructured text using AI and Amazon Comprehend

Create a chatbot and interact with it using speech and text input

Retrieve external data via your chatbot

Develop a natural language interface

Apply AI to images and videos with Amazon Rekognition

Who Should Attend

Machine Learning with AWS is ideal for data scientists, programmers, and machine learning enthusiasts, who want to learn about the artificial intelligence and machine learning capabilities of the Amazon Web Services.

Target Audiences

Machine Learning with AWS is ideal for data scientists, programmers, and machine learning enthusiasts, who want to learn about the artificial intelligence and machine learning capabilities of the Amazon Web Services.

Machine Learning with AWS is? the right place to start if you are a beginner interested in learning? useful artificial intelligence (AI) and machine learning skills using? Amazon Web Services (AWS), the most popular and powerful cloud platform.? You will learn how to use AWS to transform your projects into apps that? work at high speed and are highly scalable. From natural language? processing (NLP) applications, such as language translation and? understanding news articles and other text sources, to creating chatbots? with both voice and text interfaces, you will learn all that there is? to know about using AWS to your advantage. You will also understand how? to process huge numbers of images fast and create machine learning? models.

By the end of this course, you will have developed the skills you need? to efficiently use AWS in your machine learning and artificial? intelligence projects.?

About the Author

Jeffrey Jackovich, is the author of this course, and a curious data scientist with a background in health-tech and mergers and acquisitions (M&A). He has extensive business-oriented healthcare knowledge, but enjoys analyzing all types of data with R and Python. He loves the challenges involved in the data science process, and his ingenious demeanor was tempered while serving as a Peace Corps volunteer in Morocco. He is completing a Masters of Science in Computer Information Systems, with a Data Analytics concentration, from Boston University.?

Ruze Richards, is the author of this course, and a data scientist and cloud architect who has spent most of his career building high-performance analytics systems for enterprises and startups. He is especially passionate about AI and machine learning, having started life as a physicist who got excited about neural nets, then going on to work at AT&T Bell Labs in order to further pursue this area of interest. With the new wave of excitement along with the actual computing power being available on the cloud for anybody to actually get amazing results with machine learning, he is thrilled to be able to spread the knowledge and help people achieve their goals.?

Kesha Williams is a software engineer with over 20 years of experience? in web application development. She is specialized in working with Java,? Spring, Angular, and Amazon Web Services (AWS). She has trained and? mentored thousands of developers in the US, Europe, and Asia while? teaching Java at the university level. She has won the Ada Lovelace? Award in Computer Engineering from LookFar and the Think Different? Innovation Award from Chick-fil-A for working with emerging technologies? and artificial intelligence.? ?

Course Curriculum

Chapter 1: Introduction to Amazon Web Services

Lecture 1: Course Overview

Lecture 2: Lesson Introduction

Lecture 3: Amazon Web Services

Lecture 4: Amazon S3

Lecture 5: Core S3 Concepts

Lecture 6: AWS Command Line Interface (CLI)

Lecture 7: Summary

Chapter 2: Summarizing Text Documents Using NLP

Lecture 1: Lesson Introduction

Lecture 2: Using Amazon Comprehend

Lecture 3: Amazon Comprehend Supported Languages

Lecture 4: Extracting Information in a Set of Documents

Lecture 5: Detecting Key Phrases and Sentiments

Lecture 6: What is Lambda Function?

Lecture 7: Setting up Lambda Function

Lecture 8: Summary

Chapter 3: Perform Topic Modelling and Theme Extraction

Lecture 1: Lesson Introduction

Lecture 2: Extracting and Analyzing Common Themes

Lecture 3: Topic Modeling with Latent Dirichlet Allocation (LDA)

Lecture 4: Topic Modeling Guidelines

Lecture 5: Summary

Chapter 4: Creating Chatbot with Natural Language

Lecture 1: Lesson Introduction

Lecture 2: What is a Chatbot?

Lecture 3: Creating a Chatbot with Natural Language

Lecture 4: Lambda Function

Lecture 5: Summary

Chapter 5: Using Speech with the Chatbot

Lecture 1: Lesson Introduction

Lecture 2: Amazon Connect Basics

Lecture 3: Using Amazon Lex Chatbots with Amazon Connect

Lecture 4: Contact Flow Templates

Lecture 5: Summary

Chapter 6: Analyzing Images with Computer Vision

Lecture 1: Lesson Introduction

Lecture 2: Amazon Rekognition Basics

Lecture 3: Rekognition and Deep Learning

Lecture 4: Facial Analysis and Celebrity Recognition

Lecture 5: Face Comparison and Text in Images

Lecture 6: Summary

Instructors

Packt Publishing
Tech Knowledge in Motion

Rating Distribution

1 stars: 3 votes

2 stars: 2 votes

3 stars: 4 votes

4 stars: 5 votes

5 stars: 8 votes

Frequently Asked Questions

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