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27. Class Fields & Methods
Mike explains how classes are used in JavaScript and how TypeScript adds additional features and syntax to define class fields, methods, and static fields. A demonstration of the use of static blocks, a recent addition to TypeScript and JavaScript, for class-level setup is also provided in this segment.
- https://www.typescript-training.com/course/fundamentals-v4/11-classes/
#lesson
Mike explains how classes are used in JavaScript and how TypeScript adds additional features and syntax to define class fields, methods, and static fields. A demonstration of the use of static blocks, a recent addition to TypeScript and JavaScript, for class-level setup is also provided in this segment.
- https://www.typescript-training.com/course/fundamentals-v4/11-classes/
#lesson
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28. Access Modifiers
Mike demonstrates how to use access modifier keywords like private and protected in TypeScript to control the visibility and accessibility of class properties and methods. The difference between private and protected, and how to define private and protected fields and methods in a class are also covered in this segment.
#lesson
Mike demonstrates how to use access modifier keywords like private and protected in TypeScript to control the visibility and accessibility of class properties and methods. The difference between private and protected, and how to define private and protected fields and methods in a class are also covered in this segment.
#lesson
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29. Param Properties & Overrides
Mike explains that param properties allow for the creation of class fields and constructor parameters with the same names, reducing the noise in class definitions. The use of the "override" keyword in TypeScript to indicate that a method in a subclass is intended to override a method in the base class, helping with refactoring and catching misspellings, is also discussed.
#lesson
Mike explains that param properties allow for the creation of class fields and constructor parameters with the same names, reducing the noise in class definitions. The use of the "override" keyword in TypeScript to indicate that a method in a subclass is intended to override a method in the base class, helping with refactoring and catching misspellings, is also discussed.
#lesson
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30. Type Guards
Mike discusses type guards, which are code snippets that allow the type system to make inferences about the type of a value at runtime. Examples of built-in type guards such as `instanceof`, `typeof`, and truthy-falsey checks, as well as how to define user-defined type guards are also covered in this segment.
- https://www.typescript-training.com/course/fundamentals-v4/12-type-guards/
#lesson
Mike discusses type guards, which are code snippets that allow the type system to make inferences about the type of a value at runtime. Examples of built-in type guards such as `instanceof`, `typeof`, and truthy-falsey checks, as well as how to define user-defined type guards are also covered in this segment.
- https://www.typescript-training.com/course/fundamentals-v4/12-type-guards/
#lesson
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31. When to Use Generics
Mike introduces generics that allow for parameterizing types and creating more reusable types and provides an example of creating a dictionary from an array of objects. Solving this problem using generics, and how to define a type parameter and use it to create a more flexible and type-safe solution are also covered in this segment.
- https://www.typescript-training.com/course/fundamentals-v4/13-generics/
#lesson
Mike introduces generics that allow for parameterizing types and creating more reusable types and provides an example of creating a dictionary from an array of objects. Solving this problem using generics, and how to define a type parameter and use it to create a more flexible and type-safe solution are also covered in this segment.
- https://www.typescript-training.com/course/fundamentals-v4/13-generics/
#lesson
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32. Generics Best Practices
Mike gives advice on best practices for using type parameters in TypeScript functions. An example of a function with two generic types and a demonstration of how inference works for both type parameters are also provided this segment.
#lesson
Mike gives advice on best practices for using type parameters in TypeScript functions. An example of a function with two generic types and a demonstration of how inference works for both type parameters are also provided this segment.
#lesson
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33. Dictionary Exercise
Mike provides a challenge for students to write functions that mimic the behavior of map, filter, and reduce functions but for dictionaries instead of lists. Sample data and an interface for a dictionary are provided, and the goal is to write these functions so that they pass a test suite.
- https://www.typescript-training.com/course/fundamentals-v4/14-dict-map-filter-reduce/
#lesson
Mike provides a challenge for students to write functions that mimic the behavior of map, filter, and reduce functions but for dictionaries instead of lists. Sample data and an interface for a dictionary are provided, and the goal is to write these functions so that they pass a test suite.
- https://www.typescript-training.com/course/fundamentals-v4/14-dict-map-filter-reduce/
#lesson
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34. Wrapping Up
Mike wraps up the course by providing a recap of the topics covered in the TypeScript fundamentals course. A practice exercise for the students to write their own map, filter, and reduce utility functions is also discussed.
#lesson
Mike wraps up the course by providing a recap of the topics covered in the TypeScript fundamentals course. A practice exercise for the students to write their own map, filter, and reduce utility functions is also discussed.
#lesson
Title: Build AI-Powered Apps with OpenAI and Node.js
Description: Integrate Node.js with OpenAI to build advanced AI-powered applications. Learn to build AI chat interfaces, semantic search, document QA, function calling, and create AI images!
Link: https://frontendmasters.com/courses/openai-node/
Time: 3 hours, 34 minutes
Lessons: 22 / 22
Tags: #course #frontendmasters #720p
Description: Integrate Node.js with OpenAI to build advanced AI-powered applications. Learn to build AI chat interfaces, semantic search, document QA, function calling, and create AI images!
Link: https://frontendmasters.com/courses/openai-node/
Time: 3 hours, 34 minutes
Lessons: 22 / 22
Tags: #course #frontendmasters #720p
Frontendmasters
Advanced AI Application Development with OpenAI and Node.js | Hands-On Course with Scott Moss
Integrate Node.js with OpenAI to build advanced AI-powered applications. Learn to build AI chat interfaces, semantic search, document QA, function calling, and create AI images!
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1. Introduction
Scott Moss introduces and provides an overview of the course notes and code repository.
- https://github.com/frontendmasters/ai-nodejs
#lesson
Scott Moss introduces and provides an overview of the course notes and code repository.
- https://github.com/frontendmasters/ai-nodejs
#lesson
❤1
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2. Course Overview
Scott talks about the current state of AI and provides an overview of the course content, including building a chat experience, semantic search, document QA, and function calling. The requirements for the course are Node.js and having an OpenAI API key. The course will mainly focus on using OpenAI but will discuss on other models and services.
#lesson
Scott talks about the current state of AI and provides an overview of the course content, including building a chat experience, semantic search, document QA, and function calling. The requirements for the course are Node.js and having an OpenAI API key. The course will mainly focus on using OpenAI but will discuss on other models and services.
#lesson
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3. Intro to LLMs
Scott introduces Large Language Models (LLMs) and explains what they are and how they work. The role of these models in the AR world and the use cases for LLMs, such as writing, content creation, customer support, research, and education, are also discussed.
#lesson
Scott introduces Large Language Models (LLMs) and explains what they are and how they work. The role of these models in the AR world and the use cases for LLMs, such as writing, content creation, customer support, research, and education, are also discussed.
#lesson
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4. Setup Node & OpenAI API
Scott sets up the project and installs the necessary dependencies. They then explain how to set up the API key using a .env file and demonstrate how to import and use the OpenAI library. They show how to make a chat request to the AI and log the response. The instructor also discusses the concept of tokens and how they affect the cost and response of the AI. They demonstrate how to send messages to the AI and receive responses, and explain the limitations of chat models in terms of memory and non-determinism. Finally, they introduce the concept of a chatbot and explain the difference between the code they have written and a chatbot.
#lesson
Scott sets up the project and installs the necessary dependencies. They then explain how to set up the API key using a .env file and demonstrate how to import and use the OpenAI library. They show how to make a chat request to the AI and log the response. The instructor also discusses the concept of tokens and how they affect the cost and response of the AI. They demonstrate how to send messages to the AI and receive responses, and explain the limitations of chat models in terms of memory and non-determinism. Finally, they introduce the concept of a chatbot and explain the difference between the code they have written and a chatbot.
#lesson
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5. Simple AI Chat in Node.js
Scott creates a Node command-line chat interface using the OpenAI GPT-3 model. The readline module reads input from the command line, and a recursive function continuously prompts the user for input and generates responses from the AI model.
#lesson
Scott creates a Node command-line chat interface using the OpenAI GPT-3 model. The readline module reads input from the command line, and a recursive function continuously prompts the user for input and generates responses from the AI model.
#lesson
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6. Scaling Chat & AI Temperature
Scott explains the scaling issues that come with chat-based applications. Token limits, memory constraints, and the need for creative solutions to handle these limitations are discussed.
#lesson
Scott explains the scaling issues that come with chat-based applications. Token limits, memory constraints, and the need for creative solutions to handle these limitations are discussed.
#lesson
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7. Search & Langchain Overview
Scott introduces semantic search, which goes beyond simple string matching to understand the meaning and context of words. Scott shares some examples of semantic search in action, such as autocomplete suggestions and recommendation systems. Langchain is introduced, and the semantic search feature in the documentation is demonstrated.
#lesson
Scott introduces semantic search, which goes beyond simple string matching to understand the meaning and context of words. Scott shares some examples of semantic search in action, such as autocomplete suggestions and recommendation systems. Langchain is introduced, and the semantic search feature in the documentation is demonstrated.
#lesson
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8. Embeddings & Vectors
Scott introduces word embeddings and vectors and describes how embeddings are collections of vectors that represent the meaning behind words. Embeddings are useful for storing and comparing the meanings of words and are essential for semantic search.
#lesson
Scott introduces word embeddings and vectors and describes how embeddings are collections of vectors that represent the meaning behind words. Embeddings are useful for storing and comparing the meanings of words and are essential for semantic search.
#lesson
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9. Creating a Semantic Search
Scott provides an example of how semantic search can be used to find movies with similar themes. A movie recommendation semantic search application is created, and the initial required libraries are imported. A createStore method is written to return an in-memory vector store from a list of movie documents.
#lesson
Scott provides an example of how semantic search can be used to find movies with similar themes. A movie recommendation semantic search application is created, and the initial required libraries are imported. A createStore method is written to return an in-memory vector store from a list of movie documents.
#lesson
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10. Performing a Similarity Search
Scott codes the search function, which converts a query into an embedding and uses cosine similarity to compare it with other embeddings. The score of each search result is displayed demonstrating the proximity of each result.
#lesson
Scott codes the search function, which converts a query into an embedding and uses cosine similarity to compare it with other embeddings. The score of each search result is displayed demonstrating the proximity of each result.
#lesson
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11. Scaling Semantic Search
Scott discusses the challenges and considerations when deploying and scaling semantic search. Challenges include handling large volumes of data, updating and maintaining indexes and embeddings, ensuring query accuracy, optimizing for speed and accuracy, and using caching and feedback loops.
#lesson
Scott discusses the challenges and considerations when deploying and scaling semantic search. Challenges include handling large volumes of data, updating and maintaining indexes and embeddings, ensuring query accuracy, optimizing for speed and accuracy, and using caching and feedback loops.
#lesson
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12. Document QA Systems
Scott introduces document QA (Question Answering) and compares it with semantic search. Document QA systems provide direct answers to questions, rather than just returning links like search engines. Use cases for document QA systems are discussed as well as benefits including efficiency, accuracy, and scalability.
#lesson
Scott introduces document QA (Question Answering) and compares it with semantic search. Document QA systems provide direct answers to questions, rather than just returning links like search engines. Use cases for document QA systems are discussed as well as benefits including efficiency, accuracy, and scalability.
#lesson