Update TOC and other stuff

Author: mr-pylin

README.md

@@ -1,75 +1,108 @@
 # 🔢 NumPy Workshop
 An in-depth guide to mastering NumPy, covering fundamental to advanced array operations for data science and numerical computing.
 
-## 📋 Table of Contents
-0. [Array](./codes/00_array.ipynb)
- - Introduction to NumPy arrays
-1. [Arithmetic Operations](./codes/01_arithmetic-operations.ipynb)
- - Arithmetic operations
- - Operations between (array & scalar) and (array & array)
-2. [Comparative Operations](./codes/02_comparative-operations.ipynb)
- - Comparative operations
- - Operations between (array & scalar) and (array & array)
-3. [Index & Slice](./codes/03_index-&-slice.ipynb)
- - Indexing and slicing arrays
- - Advanced indexing techniques
- - Mask & Filters
- - Integer & Boolean array indexing
-4. [Axes](./codes/04_axes.ipynb)
- - Understanding axes in NumPy
-5. [Modifications](./codes/05_modifications.ipynb)
-6. [ndarray](./codes/06_ndarray.ipynb)
-7. [Array Creation](./codes/07_array-creation.ipynb)
-8. [Mathematics](./codes/08_mathematics.ipynb)
-9. [Statistics](./codes/09_statistics.ipynb)
-10. [Sort, Search & Count](./codes/10_sort-search-count.ipynb)
-11. [Logic](./codes/11_logic.ipynb)
-12. [Set](./codes/12_set.ipynb)
-13. [Linear Algebra](./codes/13_linear-algebra.ipynb)
-14. [Structured Array](./codes/14_structured-array.ipynb)
-15. [Input/Output](./codes/15_input-output.ipynb)
-16. [Random Generator](./codes/16_random-generator.ipynb)
-17. [Fourier Transform](./codes/17_fourier-transform.ipynb)
-18. [Efficient Computing](./codes/18_efficient-computing.ipynb)
-19. [Miscellaneous](./codes/19_miscellaneous.ipynb)
-20. [Looking Ahead](./codes/20_looking-ahead.ipynb)
+## 📖 Table of Contents
+0. **[Array](./codes/00_array.ipynb)** 
+ Introduction to NumPy arrays
+0. **[Arithmetic Operations](./codes/01_arithmetic-operations.ipynb)** 
+ Arithmetic operations between (array & scalar) or (array & array)
+0. **[Comparative Operations](./codes/02_comparative-operations.ipynb)** 
+ Comparative operations between (array & scalar) or (array & array)
+0. **[Index & Slice](./codes/03_index-&-slice.ipynb)** 
+ Basic and advanced indexing and slicing arrays including Mask & Filters
+0. **[Axes](./codes/04_axes.ipynb)** 
+ Understanding use of axes in multi-dimensional arrays combined with methods [the hardest part in NumPy for newbies in my opinion]
+0. **[Array Modifications](./codes/05_array-modifications.ipynb)** 
+ Techniques for updating values, appending, inserting, reshaping, concatenating, ...
+0. **[NdArray properties & methods](./codes/06_ndarray-members.ipynb)** 
+ Comprehensive overview of properties and methods associated with NumPy arrays.
+0. **[Array Creation](./codes/07_array-creation.ipynb)** 
+ Various methods to create NumPy arrays (e.g., `numpy.array`, `numpy.zeros`, etc.).
+0. **[Mathematics](./codes/08_mathematics.ipynb)** 
+ Mathematical functions and operations available in NumPy
+0. **[Statistics](./codes/09_statistics.ipynb)** 
+ Statistical functions for data analysis (mean, median, variance, etc.).
+0. **[Sort, Search & Count](./codes/10_sort-search-count.ipynb)** 
+ Methods for sorting, searching, and counting elements in arrays.
+0. **[Logic](./codes/11_logic.ipynb)** 
+ Logical operations and boolean indexing with NumPy arrays.
+0. **[Set](./codes/12_set.ipynb)** 
+ Set operations for array elements (union, intersection, difference).
+0. **[Linear Algebra](./codes/13_linear-algebra.ipynb)** 
+ Fundamental linear algebra operations using NumPy (matrix multiplication, determinants).
+0. **[Structured Array](./codes/14_structured-array.ipynb)** 
+ Creating and manipulating structured arrays with custom data types.
+0. **[Input/Output](./codes/15_input-output.ipynb)** 
+ Techniques for reading from and writing to files using NumPy.
+0. **[Random Generator](./codes/16_random-generator.ipynb)** 
+ Generating random numbers and distributions with NumPy's random module.
+0. **[Fourier Transform](./codes/17_fourier-transform.ipynb)** 
+ Understanding and applying Fourier transforms in NumPy.
+0. **[Efficient Computing](./codes/18_efficient-computing.ipynb)** 
+ Strategies for optimizing performance and memory usage in NumPy operations.
+0. **[Miscellaneous](./codes/19_miscellaneous.ipynb)** 
+ Additional topics and advanced features in NumPy.
+0. **[Looking Ahead](./codes/20_looking-ahead.ipynb)** 
+ Introduction to *Pandas* for data manipulation and *Matplotlib* for data visualization.
+
+## 📋 Prerequisites
+ - **Programming Fundamentals**
+ - Proficiency in Python (data types, control structures, functions, etc.).
+ - My Python Workshop: [github.com/mr-pylin/python-workshop](https://github.com/mr-pylin/python-workshop)
+ - **Mathematics for Machine Learning**
+ - Linear Algebra: Vectors, matrices, matrix operations.
+ - [*Linear Algebra Review and Reference*](https://www.cs.cmu.edu/%7Ezkolter/course/linalg/linalg_notes.pdf) written by [Zico Kolter](https://zicokolter.com)
+ - [*Notes on Linear Algebra*](https://webspace.maths.qmul.ac.uk/p.j.cameron/notes/linalg.pdf) written by [Peter J. Cameron](https://cameroncounts.github.io/web)
+ - [*MATH 233 - Linear Algebra I Lecture Notes*](https://www.geneseo.edu/~aguilar/public/assets/courses/233/main_notes.pdf) written by [Cesar O. Aguilar](https://www.geneseo.edu/~aguilar/)
+ - Probability & Statistics: Probability distributions, mean/variance, etc.
+ - [*MATH1024: Introduction to Probability and Statistics*](https://www.sujitsahu.com/teach/2020_math1024.pdf) written by [Sujit Sahu](https://www.southampton.ac.uk/people/5wynjr/professor-sujit-sahu)
+
+# ⚙️ Setup
+This project was developed using Python `v3.12.3`. If you encounter issues running the specified version of dependencies, consider using this specific Python version.
 
 ## 📦 Installing Dependencies
 You can install all dependencies listed in `requirements.txt` using [pip](https://pip.pypa.io/en/stable/installation/).
 ```bash
 pip install -r requirements.txt
 ```
-**Note:** This project was developed using Python `v3.12.3`. If you encounter issues running the dependencies or code, consider using this specific Python version.
 
-## 🛠️ Usage
+## 🛠️ Usage Instructions
  - Open the root folder with [VS Code](https://code.visualstudio.com/)
  - **Windows/Linux**: `Ctrl + K` followed by `Ctrl + O`
  - **macOS**: `Cmd + K` followed by `Cmd + O`
- - Open `.ipynb` files using [Jupyter](https://jupyter.org/) extension integrated with VS Code
- - Allow Visual Studio Code to install any recommended dependencies for working with Jupyter Notebooks.
- - Jupyter is integrated with both [VS Code](https://code.visualstudio.com/) & [Google Colab](https://colab.research.google.com/)
-
-## 🔍 Find Me
-Any mistakes, suggestions, or contributions? Feel free to reach out to me at:
- - 📍[linktr.ee/mr_pylin](https://linktr.ee/mr_pylin)
- 
-I look forward to connecting with you! 
+ - Open `.ipynb` files using [Jupyter extension](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter) integrated with **VS Code**
+ - Allow **VS Code** to install any recommended dependencies for working with Jupyter Notebooks.
+ - Note: Jupyter is integrated with both **VS Code** & **[Google Colab](https://colab.research.google.com/)**
 
-## 🔗 Usefull Links
+# 🔗 Useful Links
  - **NumPy Website**:
  - The official website for NumPy, providing information, tutorials, and resources for the NumPy library
- - Link: [numpy.org](https://numpy.org/)
+ - Official site: [numpy.org](https://numpy.org/)
  - **NumPy Documentation**:
  - Comprehensive guide and reference for all functionalities and features of the NumPy library
- - Link: [numpy.org/doc](https://numpy.org/doc/)
+ - Doc: [numpy.org/doc](https://numpy.org/doc/)
  - **NumPy Source Code**:
- - Over 1500 contributers are currently working on NumPy.
+ - Over 1500 contributors are currently working on NumPy.
  - Link: [github.com/numpy/numpy](https://github.com/numpy/numpy)
  - **Looking Ahead**:
- - Pandas
- - A powerful, open-source data analysis and manipulation library for Python
- - Pandas is built on top of NumPy
- - Link: [pandas.pydata.org/](https://pandas.pydata.org/)
- - MatPlotLib
+ - **Pandas**
+ - A powerful, open-source data analysis and manipulation library built on top of NumPy for Python
+ - Official site: [pandas.pydata.org](https://pandas.pydata.org/)
+ - My Pandas Workshop: [Coming Soon](https://github.com/mr-pylin/#)
+ - **MatPlotLib**
  - A comprehensive library for creating static, animated, and interactive visualizations in Python
- - Link: [matplotlib.org](https://matplotlib.org/)
+ - Official site: [matplotlib.org](https://matplotlib.org/)
+ - My MatPlotLib Workshop: [Coming Soon](https://github.com/mr-pylin/#)
+ - **PyTorch**
+ - An open-source machine learning library for Python developed by [Meta AI](https://ai.meta.com/), used for applications such as deep learning and neural networks.
+ - Official site: [pytorch.org](https://pytorch.org/)
+ - My PyTorch Workshop: [github.com/mr-pylin/pytorch-workshop](https://github.com/mr-pylin/pytorch-workshop)
+
+# 🔍 Find Me
+Any mistakes, suggestions, or contributions? Feel free to reach out to me at:
+ - 📍[linktr.ee/mr_pylin](https://linktr.ee/mr_pylin)
+ 
+I look forward to connecting with you! 🏃‍♂️
+
+# 📄 License
+This repository is licensed under the **[MIT License](./LICENSE)**.