ch02 code ready

Author: rasbt

.convert_notebook_to_script.py

@@ -0,0 +1,78 @@
+# Simple helper script to convert
+# a Jupyter notebook to Python
+#
+# Sebastian Raschka, 2017
+
+
+import argparse
+import os
+import subprocess
+
+
+def convert(input_path, output_path):
+    subprocess.call(['jupyter', 'nbconvert', '--to', 'script',
+                     input_path, '--output', output_path])
+
+
+def cleanup(path):
+
+    skip_lines_startwith = ('Image(filename=',
+                            '# In[',
+                            '# <hr>',
+                            'from IPython.display import Image',
+                            'get_ipython()',
+                            '# <br>')
+
+    clean_content = []
+    imports = []
+    existing_imports = set()
+    with open(path, 'r') as f:
+        next(f)
+        next(f)
+        for line in f:
+            line = line.rstrip(' ')
+            if line.startswith(skip_lines_startwith):
+                continue
+            if line.startswith('import ') or (
+                    'from ' in line and 'import ' in line):
+                if 'from __future__ import print_function' in line:
+                    if line != imports[0]:
+                        imports.insert(0, line)
+                else:
+                    if line.strip() not in existing_imports:
+                        imports.append(line)
+                        existing_imports.add(line.strip())
+            else:
+                clean_content.append(line)
+
+    clean_content = ['# coding: utf-8\n\n\n'] + imports + clean_content
+
+    with open(path, 'w') as f:
+        for line in clean_content:
+            f.write(line)
+
+
+if __name__ == '__main__':
+
+    parser = argparse.ArgumentParser(
+            description='Convert Jupyter notebook to Python script.',
+            formatter_class=argparse.RawTextHelpFormatter)
+
+    parser.add_argument('-i', '--input',
+                        required=True,
+                        help='Path to the Jupyter Notebook file')
+
+    parser.add_argument('-o', '--output',
+                        required=True,
+                        help='Path to the Python script file')
+
+    parser.add_argument('-v', '--version',
+                        action='version',
+                        version='v. 0.1')
+
+    args = parser.parse_args()
+
+    convert(input_path=args.input,
+            output_path=os.path.splitext(args.output)[0])
+
+    cleanup(args.output)

ch01/ch01.ipynb

@@ -564,7 +564,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.1"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,

ch02/README.md

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+Python Machine Learning - Code Examples
+
+
+##  Chapter 2: Training Simple Machine Learning Algorithms for Classification
+
+### Chapter Outline
+
+- Artificial neurons – a brief glimpse into the early history of machine learning
+  - The formal definition of an artificial neuron
+  - The perceptron learning rule
+- Implementing a perceptron learning algorithm in Python 
+  - An object-oriented perceptron API
+  - Training a perceptron model on the Iris dataset
+- Adaptive linear neurons and the convergence of learning
+  - Minimizing cost functions with gradient descent
+  - Implementing an Adaptive Linear Neuron in Python
+  - Improving gradient descent through feature scaling
+  - Large scale machine learning and stochastic gradient descent
+- Summary
+
+### A note on using the code examples
+
+The recommended way to interact with the code examples in this book is via Jupyter Notebook (the `.ipynb` files). Using Jupyter Notebook, you will be able to execute the code step by step and have all the resulting outputs (including plots and images) all in one convenient document.
+
+![](images/jupyter-example-1.png)
+
+
+
+Setting up Jupyter Notebook is really easy: if you are using the Anaconda Python distribution, all you need to install jupyter notebook is to execute the following command in your terminal:
+
+    conda install jupyter notebook
+
+Then you can launch jupyter notebook by executing
+
+    jupyter notebook
+
+A window will open up in your browser, which you can then use to navigate to the target directory that contains the `.ipynb` file you wish to open.
+
+**More installation and setup instructions can be found in the [README.md file of Chapter 1](../ch01/README.md)**.
+
+**(Even if you decide not to install Jupyter Notebook, note that you can also view the notebook files on GitHub by simply clicking on them: [`ch02.ipynb`](ch02.ipynb))**
+
+In addition to the code examples, I added a table of contents to each Jupyter notebook as well as section headers that are consistent with the content of the book. Also, I included the original images and figures in hope that these make it easier to navigate and work with the code interactively as you are reading the book.
+
+![](images/jupyter-example-2.png)
+
+
+When I was creating these notebooks, I was hoping to make your reading (and coding) experience as convenient as possible! However, if you don't wish to use Jupyter Notebooks, I also converted these notebooks to regular Python script files (`.py` files) that can be viewed and edited in any plaintext editor.