diff --git a/2-Regression/1-Tools/README.md b/2-Regression/1-Tools/README.md index 4a57d54aa..09108fdc0 100644 --- a/2-Regression/1-Tools/README.md +++ b/2-Regression/1-Tools/README.md @@ -1,6 +1,6 @@ # Get started with Python and Scikit-Learn for Regression models -![Logistic vs. Linear Regression Infographic](https://github.com/jlooper/ml-for-beginners/blob/main/2-Regression/1-Tools/images/Linear%20vs%20Logistic%20Regression.png) +![Logistic vs. Linear Regression Infographic](./images/logistic-linear.png) > Infographic by [Dasani Madipalli](https://twitter.com/dasani_decoded) ## [Pre-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/5/) diff --git a/2-Regression/1-Tools/images/Linear vs Logistic Regression.png b/2-Regression/1-Tools/images/Linear vs Logistic Regression.png deleted file mode 100644 index 9711cbd8c..000000000 Binary files a/2-Regression/1-Tools/images/Linear vs Logistic Regression.png and /dev/null differ diff --git a/2-Regression/1-Tools/images/logistic-linear.png b/2-Regression/1-Tools/images/logistic-linear.png index 8b5ed2017..9711cbd8c 100644 Binary files a/2-Regression/1-Tools/images/logistic-linear.png and b/2-Regression/1-Tools/images/logistic-linear.png differ diff --git a/2-Regression/2-Data/README.md b/2-Regression/2-Data/README.md index 956937f11..6e039ff66 100644 --- a/2-Regression/2-Data/README.md +++ b/2-Regression/2-Data/README.md @@ -1,6 +1,6 @@ # Build a Regression Model using Scikit-Learn: Prepare and Visualize Data -> ![Data Vizualization Inforgraphic](https://github.com/jlooper/ml-for-beginners/blob/main/2-Regression/2-Data/images/3-1-Data_Visualization.png) +> ![Data Vizualization Infographic](./images/data-visualization.png) > Infographic by [Dasani Madipalli](https://twitter.com/dasani_decoded) ## [Pre-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/7/) diff --git a/2-Regression/2-Data/images/3-1-Data_Visualization.png b/2-Regression/2-Data/images/data-visualization.png similarity index 100% rename from 2-Regression/2-Data/images/3-1-Data_Visualization.png rename to 2-Regression/2-Data/images/data-visualization.png diff --git a/2-Regression/3-Linear/README.md b/2-Regression/3-Linear/README.md index e67f5d493..49acf4a7d 100644 --- a/2-Regression/3-Linear/README.md +++ b/2-Regression/3-Linear/README.md @@ -1,9 +1,9 @@ # Build a Regression Model using Scikit-Learn: Regression Two Ways -![Linear vs Polynomial Regression Infographic](https://github.com/jlooper/ml-for-beginners/blob/main/2-Regression/3-Linear/images/3-1-Linear_Vs_Polynomial_Regression_.png) +![Linear vs Polynomial Regression Infographic](./images/linear-polynomial.png) > Infographic by [Dasani Madipalli](https://twitter.com/dasani_decoded) ## [Pre-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/9/) -### Introduction +### Introduction So far you have explored what regression is with sample data gathered from the pumpkin pricing dataset that we will use throughout this unit. You have also visualized it using Matplotlib. Now you are ready to dive deeper into regression for ML. In this lesson, you will learn more about two types of regression: basic linear regression and polynomial regression, along with some of the math underlying these techniques. diff --git a/2-Regression/3-Linear/images/3-1-Linear_Vs_Polynomial_Regression_.png b/2-Regression/3-Linear/images/linear-polynomial.png similarity index 100% rename from 2-Regression/3-Linear/images/3-1-Linear_Vs_Polynomial_Regression_.png rename to 2-Regression/3-Linear/images/linear-polynomial.png diff --git a/2-Regression/4-Logistic/README.md b/2-Regression/4-Logistic/README.md index 6269228b4..e7c1aa96a 100644 --- a/2-Regression/4-Logistic/README.md +++ b/2-Regression/4-Logistic/README.md @@ -31,7 +31,7 @@ Logistic Regression does not offer the same features as Linear Regression. The f There are other types of Logistic Regression, including Multinomial and Ordinal. Multinomial involves having more than one categories - "Orange, White, and Striped". Ordinal involves ordered categories, useful if we wanted to order our outcomes logically, like our pumpkins that are ordered by a finite number of sizes (mini,sm,med,lg,xl,xxl). -![Multinomial vs Ordinal](https://github.com/jlooper/ml-for-beginners/blob/main/2-Regression/4-Logistic/images/Multinomial_Vs_Ordinal.png) +![Multinomial vs Ordinal Regression](./images/multinomial-ordinal.png) > Infographic by [Dasani Madipalli](https://twitter.com/dasani_decoded) ### It's Still Linear diff --git a/2-Regression/4-Logistic/images/Multinomial_Vs_Ordinal.png b/2-Regression/4-Logistic/images/multinomial-ordinal.png similarity index 100% rename from 2-Regression/4-Logistic/images/Multinomial_Vs_Ordinal.png rename to 2-Regression/4-Logistic/images/multinomial-ordinal.png diff --git a/Multinomial_Vs_Ordinal.png b/Multinomial_Vs_Ordinal.png deleted file mode 100644 index c9e87a39d..000000000 Binary files a/Multinomial_Vs_Ordinal.png and /dev/null differ diff --git a/README.md b/README.md index 0aa7325a5..dc76aa777 100644 --- a/README.md +++ b/README.md @@ -84,7 +84,7 @@ By ensuring that the content aligns with projects, the process is made more enga | 21 | Power Usage in India ⚡️ | [Time Series]() | tbd | [lesson]() | Francesca | | 22 | Introduction to Reinforcement Learning | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry | | 23 | Help Peter avoid the Wolf! 🐺 | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry | -| 24 | Real-World ML Scenarios and Applications | The Future of Machine Learning | Interesting and Revealing real-world applications of ML | [lesson](8-Real-World/2-Applications/README.md) | All | +| 24 | Real-World ML Scenarios and Applications | ML in the Wild | Interesting and Revealing real-world applications of classical ML | [lesson](8-Real-World/2-Applications/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`. diff --git a/index.html b/index.html index 5b61826a4..2e3b24023 100644 --- a/index.html +++ b/index.html @@ -3,7 +3,7 @@ - Document + Machine Learning for Beginners