Merge pull request #3 from vmcf-konfmi/dev

adding presentations

.vs/ProjectSettings.json

@@ -0,0 +1,3 @@
+{
+  "CurrentProjectSetting": null
+}

README.md

@@ -1,5 +1,7 @@
 # Advanced Image Analysis (MB100T01)
 
+You can find the book on [https://vmcf-konfmi.github.io/MB100T01/intro.html](https://vmcf-konfmi.github.io/MB100T01/intro.html).
+
 This cookiecutter creates a simple boilerplate for a Jupyter Book.
 
 ## Usage
@@ -10,11 +12,11 @@ If you'd like to develop and/or build the Advanced Image Analysis (MB100T01) boo
 
 1. Clone this repository
 2. Run `pip install -r requirements.txt` (it is recommended you do this within a virtual environment)
-3. (Optional) Edit the books source files located in the `advanced_image_analysis_(mb100t01)/` directory
-4. Run `jupyter-book clean advanced_image_analysis_(mb100t01)/` to remove any existing builds
-5. Run `jupyter-book build advanced_image_analysis_(mb100t01)/`
+3. (Optional) Edit the books source files located in the `advanced_image_analysis_mb100t01/` directory
+4. Run `jupyter-book clean advanced_image_analysis_mb100t01/` to remove any existing builds
+5. Run `jupyter-book build advanced_image_analysis_mb100t01/`
 
-A fully-rendered HTML version of the book will be built in `advanced_image_analysis_(mb100t01)/_build/html/`.
+A fully-rendered HTML version of the book will be built in `gh-pages` branch.
 
 ### Hosting the book
 

advanced_image_analysis_mb100t01/00_python/00_Python_prez.md

@@ -0,0 +1,39 @@
+# Python
+
+This section focuses on introduction to Python. Python is a versatile and beginner-friendly programming language widely used in various fields, including computer science, data science, web development, and artificial intelligence.
+
+## Key Points
+
+1. **Readable and Easy to Learn:**
+   - Python is designed for simplicity and readability, making it easy for beginners to understand.
+
+2. **Interpreted Language:**
+   - Python is interpreted, allowing you to run code without a separate compilation step, making development faster and more interactive.
+
+3. **General-Purpose:**
+   - Python is a general-purpose language suitable for diverse applications, from web development to scripting.
+
+4. **Extensive Standard Library:**
+   - Python comes with a rich standard library, reducing the need for writing code from scratch for common tasks.
+
+5. **Community Support:**
+   - A large and active community provides resources, tutorials, and forums for support and collaboration.
+
+6. **Object-Oriented Programming:**
+   - Python supports object-oriented programming, organizing code in a modular way.
+
+7. **Versatility in Application:**
+   - Used in web development (Django, Flask), data science (NumPy, TensorFlow), and more, making it versatile for different career paths.
+
+8. **Cross-Platform Compatibility:**
+   - Compatible with major operating systems (Windows, macOS, Linux), ensuring code can run on different platforms without modification.
+
+## Conclusion
+
+In summary, Python is a beginner-friendly, versatile, and powerful programming language, providing a solid foundation for learning how to program. Its simplicity, readability, and extensive community support make it an excellent choice for beginners.
+
+
+We will use these presentations:
+ * [Python_basics](./Python_basics.pdf)
+ * [Python_algorithms](./Python_algorithms.pdf)
+ * [Short - KONFMI_prez_Python](./KONFMI_prez_Python.pdf)

advanced_image_analysis_mb100t01/01_pandas_statistics/intro.md

@@ -12,10 +12,7 @@ To get the most of this and the follwoing chapters' content running in your comp
  * statannotations (for adding statistical test results to plots)
  * scikit_posthocs (for post-tests)
 
-Open a terminal, activate the environment and install the necessary additional packages by running the commands below:
 
-```
-mamba activate devbio-napari-env
-
-pip install scikit_posthocs statannotations watermark pivottablejs seaborn==0.12.2
-```
+We will use these two presentations:
+ * [Tabular_Data](./Tabular_Data.pdf)
+ * [Statistics](./Statistics.pdf)

advanced_image_analysis_mb100t01/02_plotting/intro.md

@@ -5,3 +5,7 @@ This part will teach you how to plot data with matplotlib and seaborn. We start
 We then look at sophisticated and stylish plots straight from pandas dataframes. You will learn how to plot scatter plots, boxplots, distribution plots and even multivariate plots. We also show how to add statistical annotations to your plots as a convenient way to display statistical test results on the figures.
 
 Finally, you will employ all the tools learned during the previous sections to work on a complete image analysis workflow, from reading raw images, through image processing and feature extraction, to displaying your data analysis results in figures.
+
+We will use these two presentations:
+ * [Preparing Visuals of Data Analysis DV](./Preparing Visuals of Data Analysis DV.pdf)
+ * [Plotting](./Plotting.pdf)

advanced_image_analysis_mb100t01/_toc.yml

@@ -12,6 +12,7 @@ parts:
     chapters:
       - file: 00_python/00_python_intro
         sections:
+          - file: 00_python/00_Python_prez
           - file: 00_python/01_Python_Basics