diff --git a/README.md b/README.md
index a8b9faf..5422271 100644
--- a/README.md
+++ b/README.md
@@ -35,7 +35,7 @@ A list of notebooks and articles related to large language models.
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 | Merge LLMs with Mergekit | Combine multiple LLMs and create your own Frankenstein models | [Tweet](https://twitter.com/maximelabonne/status/1740732104554807676) | <a href="https://colab.research.google.com/drive/1_JS7JKJAQozD48-LhYdegcuuZ2ddgXfr?usp=sharing"><img src="images/colab.svg" alt="Open In Colab"></a> |
 | Decoding Strategies in Large Language Models | A guide to text generation from beam search to nucleus sampling | [Article](https://mlabonne.github.io/blog/posts/2022-06-07-Decoding_strategies.html) | <a href="https://colab.research.google.com/drive/19CJlOS5lI29g-B3dziNn93Enez1yiHk2?usp=sharing"><img src="images/colab.svg" alt="Open In Colab"></a> |
-| Visualizing GPT-2's Loss Landscape | 3D plot of the loss landscape based on weight pertubations. | [Tweet](https://twitter.com/maximelabonne/status/1667618081844219904) | <a href="https://colab.research.google.com/drive/1Fu1jikJzFxnSPzR_V2JJyDVWWJNXssaL?usp=sharing"><img src="images/colab.svg" alt="Open In Colab"></a> |
+| Visualizing GPT-2's Loss Landscape | 3D plot of the loss landscape based on weight perturbations. | [Tweet](https://twitter.com/maximelabonne/status/1667618081844219904) | <a href="https://colab.research.google.com/drive/1Fu1jikJzFxnSPzR_V2JJyDVWWJNXssaL?usp=sharing"><img src="images/colab.svg" alt="Open In Colab"></a> |
 | Improve ChatGPT with Knowledge Graphs | Augment ChatGPT's answers with knowledge graphs. | [Article](https://mlabonne.github.io/blog/posts/Article_Improve_ChatGPT_with_Knowledge_Graphs.html) | <a href="https://colab.research.google.com/drive/1mwhOSw9Y9bgEaIFKT4CLi0n18pXRM4cj?usp=sharing"><img src="images/colab.svg" alt="Open In Colab"></a> |
 
 ## 🧩 LLM Fundamentals
@@ -75,7 +75,7 @@ Python is a powerful and flexible programming language that's particularly good
 
 - [Real Python](https://realpython.com/): A comprehensive resource with articles and tutorials for both beginner and advanced Python concepts.
 - [freeCodeCamp - Learn Python](https://www.youtube.com/watch?v=rfscVS0vtbw): Long video that provides a full introduction into all of the core concepts in Python.
-- [Python Data Science Handbook](https://jakevdp.github.io/PythonDataScienceHandbook/): Free digital book that is a great resource for learning pandas, NumPy, matplotlib, and Seaborn.
+- [Python Data Science Handbook](https://jakevdp.github.io/PythonDataScienceHandbook/): Free digital book that is a great resource for learning pandas, NumPy, Matplotlib, and Seaborn.
 - [freeCodeCamp - Machine Learning for Everybody](https://youtu.be/i_LwzRVP7bg): Practical introduction to different machine learning algorithms for beginners.
 - [Udacity - Intro to Machine Learning](https://www.udacity.com/course/intro-to-machine-learning--ud120): Free course that covers PCA and several other machine learning concepts.