Moves python scripts to assets folder

Author: M.Notter

_posts/2023-10-23-01_scikit_simple.md

@@ -9,19 +9,19 @@ This post is part of a comprehensive machine learning series that takes you from
 
 1. **Getting Started with Machine Learning** (Current Post)
    Basic classification using Scikit-learn with the MNIST dataset
-   ([View code]({{ site.baseurl }}/scripts/01_scikit_simple.py))
+   ([View code]({{ site.baseurl }}/assets/scripts/01_scikit_simple.py))
 
 2. **Deep Learning Fundamentals**
    Introduction to neural networks using TensorFlow
-   ([View code]({{ site.baseurl }}/scripts/02_tensorflow_simple.py))
+   ([View code]({{ site.baseurl }}/assets/scripts/02_tensorflow_simple.py))
 
 3. **Advanced Machine Learning**
    Complex regression pipelines with Scikit-learn
-   ([View code]({{ site.baseurl }}/scripts/03_scikit_advanced.py))
+   ([View code]({{ site.baseurl }}/assets/scripts/03_scikit_advanced.py))
 
 4. **Advanced Deep Learning**
    Sophisticated neural network architectures in TensorFlow
-   ([View code]({{ site.baseurl }}/scripts/04_tensorflow_advanced.py))
+   ([View code]({{ site.baseurl }}/assets/scripts/04_tensorflow_advanced.py))
 
 Each tutorial builds upon concepts from previous posts while introducing new techniques and best practices. Whether you're new to machine learning or looking to expand your skills, this series provides hands-on experience with real-world datasets and modern ML tools.
 

_posts/2023-10-23-02_tensorflow_simple.md

@@ -8,7 +8,7 @@ description: Building your first neural network for image classification
 
 In this second part of our machine learning series, we'll implement the same MNIST classification task using [TensorFlow](https://www.tensorflow.org/). While Scikit-learn excels at classical machine learning, TensorFlow shines when building neural networks. We'll see how deep learning approaches differ from traditional methods and learn the basic concepts of neural network architecture.
 
-The complete code for this tutorial can be found in the [02_tensorflow_simple.py]({{ site.baseurl }}/scripts/02_tensorflow_simple.py) script.
+The complete code for this tutorial can be found in the [02_tensorflow_simple.py]({{ site.baseurl }}/assets/scripts/02_tensorflow_simple.py) script.
 
 ### Why Neural Networks?
 

_posts/2023-10-23-03_scikit_advanced.md

@@ -8,7 +8,7 @@ description: Exploring complex regression problems and preprocessing pipelines
 
 In this third part of our series, we'll explore more sophisticated machine learning techniques using [Scikit-learn](https://scikit-learn.org/stable/). While Parts 1 and 2 focused on classification, we'll now tackle regression problems and learn how to build complex preprocessing pipelines. We'll use the California Housing dataset to demonstrate these concepts.
 
-The complete code for this tutorial can be found in the [03_scikit_advanced.py]({{ site.baseurl }}/scripts/03_scikit_advanced.py) script.
+The complete code for this tutorial can be found in the [03_scikit_advanced.py]({{ site.baseurl }}/assets/scripts/03_scikit_advanced.py) script.
 
 **Note**: The purpose of this post is to highlight the flexibility and capabilities of scikit-learn's advanced features. Therefore, this tutorial focuses on introducing you to those advanced routines rather than creating the optimal regression model.
 

_posts/2023-10-23-04_tensorflow_advanced.md

@@ -7,7 +7,7 @@ description: Implementing sophisticated neural networks for regression tasks
 
 In this final part of our series, we'll explore advanced TensorFlow concepts by building a sophisticated regression model. While Part 2 introduced basic neural networks for classification, we'll now tackle regression and demonstrate TensorFlow's powerful features for model customization and optimization. However, as in part 3, the purpose of this tutorial is to highlight the flexibility and capabilities of TensorFlow. Therefore, this showcase is mostly about introducing you to those advanced routines and not about how to create the best regression model.
 
-The complete code for this tutorial can be found in the [04_tensorflow_advanced.py]({{ site.baseurl }}/scripts/04_tensorflow_advanced.py) script.
+The complete code for this tutorial can be found in the [04_tensorflow_advanced.py]({{ site.baseurl }}/assets/scripts/04_tensorflow_advanced.py) script.
 
 ### Why Advanced Neural Networks?