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Search results 25 - 48 of 69- HANDS-ON LABCalculated Systems
Evaluating Binary Classification ModelsIntermediateDuration: Up to 1 hourAuthor: Calculated Systems; Difficulty: Intermediate; Description: This lab will walk you through building several binary classification models using different model methodologies and then comparing the model predictions using evaluation tools.; Duration: Up to 1 hour; Content Topics: Machine Learning; This hands-on lab has: 4 Lab steps - HANDS-ON LABCalculated Systems
Testing Your Models in the Real WorldBeginnerDuration: Up to 1 hourAuthor: Calculated Systems; Difficulty: Beginner; Description: How do you know that your models will do a good job making predictions on new, unseen data? This lab will discuss the fundamentals.; Duration: Up to 1 hour; This hands-on lab has: 4 Lab steps - HANDS-ON LABCalculated Systems
Getting Started with Natural Language ProcessingBeginnerDuration: Up to 1 hourAuthor: Calculated Systems; Difficulty: Beginner; Description: This lab is aimed at machine learning beginners who want to gain a familiarity with Natural Language Processing (NLP) concepts.; Duration: Up to 1 hour; Content Topics: Amazon Web Services; This hands-on lab has: 3 Lab steps - HANDS-ON LABStefano Cascavilla
Analyze and Retrieve Information from Text Using Google Cloud Natural LanguageIntermediateDuration: Up to 45 minutesAuthor: Stefano Cascavilla; Difficulty: Intermediate; Duration: Up to 45 minutes; Content Topics: Google Cloud Platform; This hands-on lab has: 5 Lab steps - HANDS-ON LABAndrea Giussani
Introduction to Financial Data Manipulation with PythonBeginnerDuration: Up to 1 hourAuthor: Andrea Giussani; Difficulty: Beginner; Description: The goal of this lab is to consolidate your data management and manipulation skills using Python.; Duration: Up to 1 hour; Content Topics: Development, Analytics; This hands-on lab has: 2 Lab steps - HANDS-ON LABCalculated Systems
Moving From Spreadsheet to DatabaseBeginnerDuration: Up to 1 hour and 20 minutesAuthor: Calculated Systems; Difficulty: Beginner; Description: This lab is aimed at beginners who want to move beyond spreadsheets and migrate their data into a database.; Duration: Up to 1 hour and 20 minutes; Content Topics: Amazon Web Services; This hands-on lab has: 3 Lab steps - HANDS-ON LABJun Fritz
Enhancing Generative AI Models With Retrieval-Augmented Generation (RAG)BeginnerDuration: Up to 30 minutesAuthor: Jun Fritz; Difficulty: Beginner; Description: Learn the fundamentals of Retrieval-Augmented Generation (RAG) and how to enhance the accuracy of generative AI models in this hands-on lab.; Duration: Up to 30 minutes; Content Topics: Development, Artificial Intelligence; This hands-on lab has: 2 Lab steps - LAB CHALLENGEThomas Holmes
Using Python to Cleanse and Rationalize Data ChallengeBeginnerDuration: Up to 2 hours and 30 minutesAuthor: Thomas Holmes; Difficulty: Beginner; Description: You will put your basic knowledge of Python to work in this lab challenge in order to perform a simple form of data cleansing on text.; Duration: Up to 2 hours and 30 minutes; Content Topics: Development; This lab challenge has: 2 Lab steps - HANDS-ON LABJun Fritz
Implementing Safeguards for AI Applications With Amazon Bedrock GuardrailsBeginnerDuration: Up to 30 minutesAuthor: Jun Fritz; Difficulty: Beginner; Description: Configure an Amazon Bedrock Guardrail to ensure safe, responsible interactions with your AI applications in this hands-on lab.; Duration: Up to 30 minutes; This hands-on lab has: 2 Lab steps - HANDS-ON LABJun Fritz
Orchestrating Generative AI Applications With AWS Step Functions and Amazon BedrockIntermediateDuration: Up to 1 hour and 15 minutesAuthor: Jun Fritz; Difficulty: Intermediate; Description: Learn how to perform AI prompt-chaining and integrate Amazon Bedrock with AWS Step Functions in this hands-on lab.; Duration: Up to 1 hour and 15 minutes; Content Topics: Development, Artificial Intelligence; This hands-on lab has: 4 Lab steps - HANDS-ON LABJun Fritz
Invoking Amazon Bedrock Models Using the Bedrock Runtime and AWS LambdaIntermediateDuration: Up to 1 hour and 15 minutesAuthor: Jun Fritz; Difficulty: Intermediate; Description: Learn how to invoke Amazon Bedrock models using the Amazon Bedrock API and AWS Lambda in this hands-on lab.; Duration: Up to 1 hour and 15 minutes; Content Topics: Amazon Web Services; This hands-on lab has: 3 Lab steps - HANDS-ON LABLogan Rakai
Introduction to the OpenAI Chat Completions APIBeginnerDuration: Up to 30 minutesAuthor: Logan Rakai; Difficulty: Beginner; Description: Learn how to use the OpenAI Chat completions API to generate text in this lab.; Duration: Up to 30 minutes; This hands-on lab has: 1 Lab step - HANDS-ON LABAndrew Burchill
Analyzing Sentiments and Entities in Text with Amazon ComprehendBeginnerDuration: Up to 50 minutesAuthor: Andrew Burchill; Difficulty: Beginner; Description: Learn how to use AWS's natural language processing service Amazon Comprehend in this hands-on laboratory.; Duration: Up to 50 minutes; Content Topics: Amazon Web Services; This hands-on lab has: 2 Lab steps - HANDS-ON LABCalculated Systems
Creating Your First Dialogflow BotBeginnerDuration: Up to 1 hourAuthor: Calculated Systems; Difficulty: Beginner; Description: Learn how to create a simulated banking concierge bot using Google DIalogflow in this lab.; Duration: Up to 1 hour; Content Topics: Artificial Intelligence; This hands-on lab has: 9 Lab steps - HANDS-ON LABLogan Rakai
Predicting Time-Series Data With Amazon ForecastBeginnerDuration: Up to 1 hour and 40 minutesAuthor: Logan Rakai; Difficulty: Beginner; Description: Analyze household energy consumption and go from raw data to accurate forecasts using the built-in algorithms provided by Amazon Forecast in this hands-on lab.; Duration: Up to 1 hour and 40 minutes; Content Topics: Amazon Web Services; This hands-on lab has: 6 Lab steps - LAB CHALLENGEAndrea Giussani
Machine Learning Python Challenge: ClassificationAdvancedDuration: Up to 1 hourAuthor: Andrea Giussani; Difficulty: Advanced; Description: The aim of this lab is to challenge you on building a supervised machine learning pipeline to predict the probability that a subject will suffer from a heart stroke.; Duration: Up to 1 hour; Content Topics: Machine Learning; This lab challenge has: 2 Lab steps - HANDS-ON LABCalculated Systems
Creating an Active Chatbot in DialogflowIntermediateDuration: Up to 1 hourAuthor: Calculated Systems; Difficulty: Intermediate; Description: In this lab, you will create a banking concierge chatbot that is capable of asking clarifying and follow-up questions.; Duration: Up to 1 hour; Content Topics: Artificial Intelligence; This hands-on lab has: 11 Lab steps - HANDS-ON LABCalculated Systems
Performing K-Means Clustering With PythonIntermediateDuration: Up to 1 hourAuthor: Calculated Systems; Difficulty: Intermediate; Description: In this lab, you'll learn how to perform K-Means Clustering on a set of data and plot the outcome.; Duration: Up to 1 hour; Content Topics: Development; This hands-on lab has: 2 Lab steps - LAB CHALLENGEMatt MartinezAzure Bot Services ChallengeIntermediateDuration: Up to 1 hour and 30 minutesAuthor: Matt Martinez; Difficulty: Intermediate; Description: Prove your practical knowledge of bots and your proficiency with the Microsoft Azure portal and CLI by creating a bot and publishing to Azure Bot Service; Duration: Up to 1 hour and 30 minutes; Content Topics: Artificial Intelligence; This lab challenge has: 2 Lab steps
- HANDS-ON LABAndrew Burchill
Streamlining Amazon SageMaker Governance With Model CardsBeginnerDuration: Up to 1 hourAuthor: Andrew Burchill; Difficulty: Beginner; Description: Learn how to create a model card to document your Amazon SageMaker machine learning models in this hands-on lab.; Duration: Up to 1 hour; Content Topics: Amazon Web Services; This hands-on lab has: 3 Lab steps - HANDS-ON LABJun Fritz
Building a PDF RAG Chatbot Powered by LangChain and Amazon BedrockIntermediateDuration: Up to 1 hour and 30 minutesAuthor: Jun Fritz; Difficulty: Intermediate; Description: Learn how to deploy a PDF Chatbot using retrieval-augmented generation (RAG), LangChain, and AWS services in this hands-on lab.; Duration: Up to 1 hour and 30 minutes; Content Topics: Amazon Web Services; This hands-on lab has: 6 Lab steps - HANDS-ON LABAndrew Burchill
Customizing Large Language Models Using OllamaBeginnerDuration: Up to 1 hourAuthor: Andrew Burchill; Difficulty: Beginner; Description: Learn how to use Ollama to run, manage, and customize Large Language Models in this hands-on lab.; Duration: Up to 1 hour; Content Topics: Management, Artificial Intelligence; This hands-on lab has: 4 Lab steps - HANDS-ON LABAndrew Burchill
Optimizing Prompts For Large Language Models Using Amazon BedrockBeginnerDuration: Up to 1 hourAuthor: Andrew Burchill; Difficulty: Beginner; Description: Learn how to engineer and develop prompts for large language models in this hands-on lab.; Duration: Up to 1 hour; Content Topics: Artificial Intelligence; This hands-on lab has: 3 Lab steps - HANDS-ON LABAdil Islam
Predict Income Levels Using Azure Machine Learning DesignerBeginnerDuration: Up to 50 minutesAuthor: Adil Islam; Difficulty: Beginner; Description: Predict income levels using census data and compare the performance of two trained models in this Azure Machine Learning Designer hands-on lab.; Duration: Up to 50 minutes; Content Topics: Microsoft Azure; This hands-on lab has: 6 Lab steps