├── _config.yml └── readme.md /_config.yml: -------------------------------------------------------------------------------- 1 | theme: jekyll-theme-modernist 2 | -------------------------------------------------------------------------------- /readme.md: -------------------------------------------------------------------------------- 1 | # Welcome to Oracle Database's GHW: AI/ML Week Challenges! 2 | 3 | Hello hackers! This week, we're going to learn how to leverage several of Oracle's database technologies through a series of fun and interactive challenges! 4 | 5 | ## Getting Help 6 | 7 | * If you have any questions about Oracle or their Global Hack Week challenges, head to the [MLH Discord](https://discord.mlh.io/) and find the #ask-oracle channel! 8 | * Each coding challenge is accompanied by a LiveLab tutorial that will walk you through each challenge step by step 9 | * If you need additional resources, you can find them at the bottom of this page! 10 | 11 | 12 | # Registration Challenges 13 | 14 | ## Registration Challenge 1 15 | ### Sign up and download 23ai VirtualBox 16 | 17 | Head over to the [VirtualBox signup page](https://mlh.link/ghwaiml824-oracle-virtualbox) to get set up with a new account. 18 |
19 | 20 | ## Registration Challenge 2 21 | ### Create an account and Sign in for LiveLabs 22 | 23 | Create a [LiveLabs account](https://mlh.link/ghwaiml824-oracle-livelabs) so you can leverage Oracle's LiveLab tutorials 24 |
25 | 26 | # Coding Challenges 27 | 28 | ## Coding Challenge 1 29 | ### Build a RAG application in 7 easy steps with LangChain and Oracle AI Vector Search 30 | #### Objectives: 31 | * Learn how to use the popular open source Python LangChain framework to search your PDF documents with natural language. 32 | * The application will load a chosen PDF document, chop it up into chunks, vectorize and index those chunks. 33 | * Build a simple ChatBot interface to allow natural language questions to be asked about data in your PDF documents. 34 | * This RAG [retrieval augmented generation] architecture is powered by Oracle AI Vector Search, a feature of Oracle Database 23ai. 35 | 36 | #### Documentation: 37 | * [Follow this step by step LiveLab to complete this challenge](https://mlh.link/ghwaiml824-oracle-rag) 38 | 39 | ## Coding Challenge 2 40 | ### An introduction to Oracle AI Vector Search using SQL 41 | #### Objectives: 42 | * Learn the fundamentals of vector search and how it can be applied to similarity search, RAG [retrieval augmented generation] and finding outliers. 43 | * Learn how to create, query and modify vectors using SQL. 44 | * See how vector search uses a ‘closest match given the available data’ approach. 45 | * See how that you can combine vector search with relational queries for advanced attribute filtering. 46 | 47 | #### Documentation: 48 | * [Follow this step by step LiveLab to complete this challenge](https://mlh.link/ghwaiml824-oracle-SQL) 49 | 50 | ## Coding Challenge 3 51 | ### Get started with Oracle Machine Learning Fundamentals on Oracle Autonomous Database 52 | #### Objectives: 53 | * Get a quick tour of Oracle Machine Learning technologies on Autonomous Database. 54 | * Use OML Notebooks to create and evaluate models and score data using SQL, Python and R. 55 | * Use OML Services REST API to deploy models and score data. Use AutoML UI for a no-code machine learning experience. 56 | 57 | #### Documentation: 58 | * [Follow this step by step LiveLab to complete this challenge](https://mlh.link/ghwaiml824-oracle-OML) 59 | 60 | ## Coding Challenge 4 61 | ### Introduction to Oracle Machine Learning for Python on Autonomous Database 62 | #### Objectives: 63 | * In this hands-on lab, experience Oracle Machine Learning for Python on Oracle Autonomous Database. 64 | * OML4Py supports scalable in-database data exploration and preparation using native Python syntax, invocation of in-database algorithms for model building and scoring, and embedded execution of user-defined Python functions from Python or REST APIs. 65 | * OML4Py also includes the AutoML interface for automated algorithms and feature selection, and hyperparameter tuning. Join us for this tour of OML4Py. 66 | 67 | #### Documentation: 68 | * [Follow this step by step LiveLab to complete this challenge](https://mlh.link/ghwaiml824-oracle-OML-python) 69 | 70 | ## Coding Challenge 5 71 | ### MySQL : Machine Learning for Beginners using HeatWave AutoML 72 | #### Objectives: 73 | * Discover how HeatWave’s built-in capabilities enable the development of machine learning models directly within the MySQL database. 74 | * HeatWave ML simplifies machine learning for both novice users and experienced practitioners. 75 | * By providing the data, HeatWave ML analyzes its characteristics and creates an optimized machine learning model for generating predictions and explanations. 76 | * In this challenge, participants will create and use a predictive machine learning model. 77 | * The process includes preparing data, training a model using the ML_TRAIN routine, and generating predictions and explanations with the ML_PREDICT_ and ML_EXPLAIN_ routines. 78 | * Finally, participants will assess the model's quality using the ML_SCORE routine and view model explanations to understand the workings of their model. 79 | * All these routines are executed within the HeatWave MySQL Database. 80 | 81 | #### Documentation: 82 | * [Follow this step by step LiveLab to complete this challenge](https://mlh.link/ghwaiml824-oracle-heatwave-automl) 83 | * [Check out this additional documentation on HeatWave](https://mlh.link/ghwaiml824-oracle-heatwave) 84 | 85 | # Resources 86 | ## Hands-On Labs 87 | * [Oracle - Discover. Learn. Build.](https://mlh.link/ghwaiml824-oracle-HOL1) 88 | * [Build an Innovative Q&A Interface Powered by Generative AI with Oracle APEX - Oracle LiveLabs](https://mlh.link/ghwaiml824-oracle-HOL2) 89 | * [Smart Project Management App with AI-Assisted Development in Oracle APEX](https://mlh.link/ghwaiml824-oracle-HOL3) 90 | * [Build AI chatbot with Oracle Database 23ai](https://mlh.link/ghwaiml824-oracle-HOL4) 91 | * [AI Vector Search - Complete RAG Application using PL/SQL in Oracle Database 23ai](https://mlh.link/ghwaiml824-oracle-HOL5) 92 | * [Easy Text Search over Multiple Tables and Views with DBMS_SEARCH in Oracle Database 23ai](https://mlh.link/ghwaiml824-oracle-HOL6) 93 | * [Oracle Database 23ai New Features](https://mlh.link/ghwaiml824-oracle-HOL7) 94 | * [SQL Empowerment in Oracle Database 23ai: Leveraging Domains and New Features](https://mlh.link/ghwaiml824-oracle-HOL8) 95 | * [SQL, JSON, and MongoDB API: Unify worlds with Oracle Database 23ai Free](https://mlh.link/ghwaiml824-oracle-HOL9) 96 | * [Simple Data Drive Applications using JavaScript in Oracle Database 23ai Free](https://mlh.link/ghwaiml824-oracle-HOL10) 97 | * [Machine Learning on ADB - Choose Your Journey](https://mlh.link/ghwaiml824-oracle-HOL11) 98 | * [Exploring JSON Relational Duality Views in Oracle Database 23ai Free with Java](https://mlh.link/ghwaiml824-oracle-HOL12) 99 | * [Autonomous Database 15 Minute Quick Start](https://mlh.link/ghwaiml824-oracle-HOL13) 100 | * [Implement Data Sharing with PL/SQL in Autonomous Database](https://mlh.link/ghwaiml824-oracle-HOL14) 101 | * [Introduction to Oracle Spatial Studio](https://mlh.link/ghwaiml824-oracle-HOL15) 102 | * [Analyze, Query and Visualize Graphs in Oracle Database](https://mlh.link/ghwaiml824-oracle-HOL16) 103 | * [Get Started with Graph Studio on Oracle Autonomous Database](https://mlh.link/ghwaiml824-oracle-HOL17) 104 | * [Load and Analyze Your Data with Autonomous Database](https://mlh.link/ghwaiml824-oracle-HOL18) 105 | 106 | ## Dev Gym 107 | * [Play SQuizL! - A mobile-friendly daily SQL challenge](https://mlh.link/ghwaiml824-oracle-devgym) 108 | 109 | ## Documentation 110 | * [AI Vector Search](https://mlh.link/ghwaiml824-oracle-DOC1) 111 | * [Oracle Machine Learning](https://mlh.link/ghwaiml824-oracle-DOC2) 112 | * [Using APEX Assistant](https://mlh.link/ghwaiml824-oracle-DOC3) 113 | * [AI-powered APEX Assistant](https://mlh.link/ghwaiml824-oracle-DOC4) 114 | * [APEX: AI-learn](https://mlh.link/ghwaiml824-oracle-DOC5) 115 | * [Database](https://mlh.link/ghwaiml824-oracle-DOC6) 116 | * [23ai](https://mlh.link/ghwaiml824-oracle-DOC7) 117 | * [OCI](https://mlh.link/ghwaiml824-oracle-DOC8) 118 | * [ADB](https://mlh.link/ghwaiml824-oracle-DOC9) 119 | * [ORDS](https://mlh.link/ghwaiml824-oracle-DOC10) 120 | * [APEX](https://mlh.link/ghwaiml824-oracle-DOC11) 121 | * [Connect to OCI MySQL Heatwave](https://mlh.link/ghwaiml824-oracle-DOC12) 122 | * [JSON Duality Views](https://mlh.link/ghwaiml824-oracle-DOC13) 123 | * [Oracle Graph](https://mlh.link/ghwaiml824-oracle-DOC14) 124 | * [Oracle Spatial](https://mlh.link/ghwaiml824-oracle-DOC15) 125 | 126 | 127 | --------------------------------------------------------------------------------