24 December, 2024
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AIQA01 – Introduction

AINLP11 – Summary

AINLP10 – Knowledge check

AINLP09 – Exercise – Analyze text

AINLP08 – Extract linked entities

AINLP07 – Extract entities

AINLP06 – Analyze sentiment

AINLP05 – Extract key phrases

AINLP04 – Detect language

AINLP03 – Provision an Azure AI Language resource

AINLP02 – Introduction

AINLP01 – Develop natural language processing solutions with Azure AI Services

AZAI8 – Understand capabilities of Azure Cognitive Search

AZAI7 – Understand capabilities of the Azure OpenAI Service

AZAI5 – Understand capabilities of Azure Machine Learning

AXIN10 _ Các video hướng dẫn có lượt view cao nhất

AXIN9 – Sử dụng Interceptors để thêm token vào mọi request

AXIN8 – Xóa dữ liệu với DELETE request

AXIN7 – Gửi dữ liệu với PUT request

AXIN6 – Gửi dữ liệu với POST request

AXIN5 – Lấy dữ liệu với nhiều yêu cầu GET đồng thời

AXIN4 – Xử lý lỗi trong các yêu cầu HTTP

AXIN3 – Thay đổi header của request trước khi gửi đi

AXIN2 – Cách thiết lập Axios Interceptors trong React

AXIN1 – Giới thiệu về Axios và Interceptors

AZAI4 – Understand considerations for AI Engineers

AZAI3 – Understand AI-related terms

AZAI02 -Define artificial intelligence

AZAI01 – Introduction

Day 5 –  Write a sentence based on  a picture

DAY 3 EMAIL

Day 2:  Write a sentence based on a picture

Day 1: Although more and more people read news on the Internet, newspapers will remain the most important source of news. Do you agree or disagree?

Test

Describe a Picture – 02

AICC01 – Introduction

Azure AI services are cloud-based services that encapsulate AI capabilities. Rather than a single product, you should think of AI services as a set of individual services that you can use as building blocks to compose sophisticated, intelligent applications. AI services includes a wide range of individual services across multiple categories, as shown in the following […]

5 mins read

AZAI9 – Knowledge check

Check your knowledge 1. Which of the following best describes the predictions made by a machine learning model?  a. Absolutely correct values based on conditional logic. b. Randomly selected values with an equal chance of selection. c. Probabilistic values based on correlations found in training data. 2. A data scientist has used Azure Machine Learning to train a machine […]

7 mins read

AIQA01 – Introduction

(Source: https://learn.microsoft.com/en-us/training/modules/create-question-answer-solution-ai-language/1-introduction) A common pattern for “intelligent” applications is to enable users to ask questions using natural language, and receive appropriate answers. In effect, this kind of solution brings conversational intelligence to a traditional frequently asked questions (FAQ) publication. In this module, you will learn how to use Azure AI Language to create a knowledge base […]

2 mins read

AINLP11 – Summary

(Source: https://learn.microsoft.com/en-us/training/modules/analyze-text-ai-language/10-summary) In this module, you learned how to use Azure AI Language to: To learn more about Azure AI Language and some of the concepts covered in this module, you can explore the following: Trong mô-đun này, bạn đã học cách sử dụng Azure AI Language để: Để tìm hiểu thêm về Azure AI Language […]

1 min read

AINLP10 – Knowledge check

(Source: https://learn.microsoft.com/en-us/training/modules/analyze-text-ai-language/9-knowledge-check) 1. How should you create an application that monitors the comments on your company’s web site and flags any negative posts?  A. Use the Azure AI Language service to extract key phrases. B. Use the Azure AI Language service to perform sentiment analysis of the comments. C. Use the Azure AI Language service to extract […]

5 mins read

AINLP09 – Exercise – Analyze text

(Source: https://learn.microsoft.com/en-us/training/modules/analyze-text-ai-language/8-exercise-analyze-text) This unit includes a lab to complete.Use the free resources provided in the lab to complete the exercises in this unit. You will not be charged for the lab environment; however, you may need to bring your own subscription depending on the lab. Microsoft provides this lab experience and related content for educational purposes. […]

5 mins read

AINLP08 – Extract linked entities

(Source: https://learn.microsoft.com/en-us/training/modules/analyze-text-ai-language/7-extract-linked-entities) In some cases, the same name might be applicable to more than one entity. For example, does an instance of the word “Venus” refer to the planet or the goddess from mythology? Entity linking can be used to disambiguate entities of the same name by referencing an article in a knowledge base. Wikipedia provides […]

3 mins read

AINLP07 – Extract entities

(Source: https://learn.microsoft.com/en-us/training/modules/analyze-text-ai-language/6-extract-entities) Named Entity Recognition identifies entities that are mentioned in the text. Entities are grouped into categories and subcategories, for example: Nhận diện thực thể được đặt tên (Named Entity Recognition) xác định các thực thể được đề cập trong văn bản. Các thực thể được nhóm vào các danh mục và phân mục, ví […]

1 min read

AINLP06 – Analyze sentiment

(Source: https://learn.microsoft.com/en-us/training/modules/analyze-text-ai-language/5-analyze-sentiment) Sentiment analysis is used to evaluate how positive or negative a text document is, which can be useful in various workloads, such as: + Evaluating a movie, book, or product by quantifying sentiment based on reviews.+ Prioritizing customer service responses to correspondence received through email or social media messaging.When using Azure AI Language to […]

4 mins read