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.
Enroll now: Beginning Machine Learning with AWS
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
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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
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