complete simple reiforcement agent example | restrcuture book structure

00 Couse Overview.md

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-## Welcome to 6.86x *Machine Learning with Python–From Linear Models to Deep Learning*.
+## Welcome to _Machine Learning with Python–From Linear Models to Deep Learning_.
 
 Machine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk.
 

INTRO.md

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+# n03@n's Machine Learning notes
+
+[Machine Learning with Python: from Linear Models to Deep Learning](https://www.edx.org/learn/machine-learning/massachusetts-institute-of-technology-machine-learning-with-python-from-linear-models-to-deep-learning)
+
+[MIT MicroMasters® Program Calendar](https://micromasters.mit.edu/ds/upcoming-dates/)
+
+**Disclaimer**: The following notes are a mesh of my own notes, forums, youtube, GPT, medium, arxiv, some useful forum threads and various course materials (standford, MIT, DeepLearning.AI, udacity etc). There may be various error and that could very well be due to my own interpretation during learning or over simplifying.
+
+---
+
+**Note:** As a prerequisite, I had to brush up some basic math important for machine learning. Here are my Jupiter notes published as [Digital Book 📚](https://N0-man.github.io/math-for-machine-learning/)
+
+![alt text](image.png)
+
+```{tableofcontents}
+
+```

README.md

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-# Learning Notes from MITx 6.86x semister
+# Learning Notes from MITx semister
 
 [Machine Learning with Python: from Linear Models to Deep Learning](https://www.edx.org/learn/machine-learning/massachusetts-institute-of-technology-machine-learning-with-python-from-linear-models-to-deep-learning)