diff --git a/3-Classification/README.md b/3-Classification/README.md index 31643651..a9713fad 100644 --- a/3-Classification/README.md +++ b/3-Classification/README.md @@ -1,12 +1,13 @@ -# Getting Started with +# Getting Started with Classification -In this section of the curriculum, you will be introduced to ... +In this section of the curriculum you will learn about how to classify data using Machine Learning. ## Topics -1. [Introduction to](1-intro-to/README.md) - - +1. [Visualize your Data and Prepare it for Use](1-Data/README.md) +2. [Build a Discriminative Model](2-Discriminative/README.md) +3. [Build a Generative Model](3-Generative/README.md) +4. [Applied ML: Build a Web App](4-Applied/README.md) ## Credits -"Introduction to" was written with ♥️ by [Name](Twitter) \ No newline at end of file +"Getting Started with Classification" was written with ♥️ by [Cassie Breviu](@cassieview) \ No newline at end of file diff --git a/README.md b/README.md index 2e363989..ea82d6e9 100644 --- a/README.md +++ b/README.md @@ -59,32 +59,32 @@ By ensuring that the content aligns with projects, the process is made more enga > **A note about quizzes**: All quizzes are contained [in this app](https://jolly-sea-0a877260f.azurestaticapps.net), for 48 total quizzes of three questions each. They are linked from within the lessons but the quiz app can be run locally; follow the instruction in the `quiz-app` folder. -| Lesson Number | Project Name/Group | Concepts Taught | Learning Objectives | Linked Lesson | Author | -| :-----------: | :--------------------------------------: | :----------------------------------: | ---------------------------------------------------------------------------------------------------- | :------------------------------------------------: | :-------: | -| 01 | [Introduction](1-Introduction/README.md) | Introduction to Machine Learning | Learn the basic concepts behind Machine Learning | [lesson](1-Introduction/1-intro-to-ML/README.md) | Amy | -| 02 | [Introduction](1-Introduction/README.md) | The History of Machine Learning | Learn the history underlying this field | [lesson](1-Introduction/2-history-of-ML/README.md) | Amy | -| 03 | Introduction to Regression | [Regression](2-Regression/README.md) | Get started with Python and Scikit-Learn for Regression models | [lesson](2-Regression/1-Tools/README.md) | Jen | -| 04 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Visualize and clean data in preparation for ML | [lesson](2-Regression/2-Data/README.md) | Jen | -| 05 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build Linear and Polynomial Regression models | [lesson](2-Regression/3-Linear/README.md) | Jen | -| 06 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build a Logistic Regression model | [lesson](2-Regression/4-Logistic/README.md) | Jen | -| 07 | Introduction to Clustering | [Clustering]() | tbd | [lesson]() | Cassie | -| 08 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie | -| 09 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie | -| 10 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie | -| 11 | Introduction to Classification | [Classification]() | | [lesson]() | Paige | -| 12 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige | -| 13 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige | -| 14 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige | -| 15 | Introduction to NLP | [Natural Language Processing]() | tbd | [lesson]() | Stephen | -| 16 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen | -| 17 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen | -| 18 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen | -| 19 | Introduction to Time Series Forecasting | [Time Series]() | tbd | [lesson]() | Francesca | -| 20 | Power Usage in India ⚡️ | [Time Series]() | tbd | [lesson]() | Francesca | -| 21 | Introduction to Reinforcement Learning | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry | -| 22 | A fancy French mousetrap 🍫 | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry | -| 23 | Future | The Ethics of Machine Learning | What are the important ethical issues apparent now and how will they impact the field going forward? | [lesson](8-Future/Ethics/README.md) | Tomomi | -| 24 | Future | The Future of Machine Learning | What are the important trends that will shape the future of ML? | [lesson](8-Future/Future-Trends/README.md) | All | +| Lesson Number | Project Name/Group | Concepts Taught | Learning Objectives | Linked Lesson | Author | +| :-----------: | :--------------------------------------: | :------------------------------------------: | ---------------------------------------------------------------------------------------------------- | :---------------------------------------------------: | :-------: | +| 01 | [Introduction](1-Introduction/README.md) | Introduction to Machine Learning | Learn the basic concepts behind Machine Learning | [lesson](1-Introduction/1-intro-to-ML/README.md) | Amy | +| 02 | [Introduction](1-Introduction/README.md) | The History of Machine Learning | Learn the history underlying this field | [lesson](1-Introduction/2-history-of-ML/README.md) | Amy | +| 03 | Introduction to Regression | [Regression](2-Regression/README.md) | Get started with Python and Scikit-Learn for Regression models | [lesson](2-Regression/1-Tools/README.md) | Jen | +| 04 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Visualize and clean data in preparation for ML | [lesson](2-Regression/2-Data/README.md) | Jen | +| 05 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build Linear and Polynomial Regression models | [lesson](2-Regression/3-Linear/README.md) | Jen | +| 06 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build a Logistic Regression model | [lesson](2-Regression/4-Logistic/README.md) | Jen | +| 07 | Introduction to Classification | [Classification](3-Classification/README.md) | Clean, Prep, and Visualize your Data; Introduction to Classification | [lesson](3-Classification/1-Data/README.md) | Cassie | +| 08 | Delicious Asian Recipes 🍜 | [Classification](3-Classification/README.md) | Build a Discriminative Model | [lesson](3-Classification/2-Descriminative/README.md) | Cassie | +| 09 | Delicious Asian Recipes 🍜 | [Classification](3-Classification/README.md) | Build a Generative Model | [lesson](3-Classification/3-Generative/README.md) | Cassie | +| 10 | Delicious Asian Recipes 🍜 | [Classification](3-Classification/README.md) | Build a Web App using your Model | [lesson](3-Classification/4-Applied/README.md) | Cassie | +| 11 | Introduction to Clustering | [Clustering](4-Clustering/README.md) | | [lesson]() | Paige | +| 12 | Interesting Maya Architecture 🦜 | [Clustering]() | | [lesson]() | Paige | +| 13 | Interesting Maya Architecture 🦜 | [Clustering]() | | [lesson]() | Paige | +| 14 | Interesting Maya Architecture 🦜 | [Clustering]() | | [lesson]() | Paige | +| 15 | Introduction to NLP | [Natural Language Processing]() | tbd | [lesson]() | Stephen | +| 16 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen | +| 17 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen | +| 18 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen | +| 19 | Introduction to Time Series Forecasting | [Time Series]() | tbd | [lesson]() | Francesca | +| 20 | Power Usage in India ⚡️ | [Time Series]() | tbd | [lesson]() | Francesca | +| 21 | Introduction to Reinforcement Learning | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry | +| 22 | A fancy French mousetrap 🍫 | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry | +| 23 | Future | The Ethics of Machine Learning | What are the important ethical issues apparent now and how will they impact the field going forward? | [lesson](8-Future/Ethics/README.md) | Tomomi | +| 24 | Future | The Future of Machine Learning | What are the important trends that will shape the future of ML? | [lesson](8-Future/Future-Trends/README.md) | All | ## Offline access You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). Fork this repo, [install Docsify](https://docsify.js.org/#/quickstart) on your local machine, and then in the root folder of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`.