chore: complete items

README.md

@@ -3,7 +3,7 @@ gitea: none
 include_toc: true
 ---
 
-# PerfSPEC Learning Phase
+# PerfSPEC Learning Phas# PerfSPEC Learning Phasee
 
 Based in [PrefSPEC: Performance Profiling-based Proactive Security Policy Enforcement for Containers](https://ieeexplore.ieee.org/document/10577533) document presented in [1], thir repository contains source files used to generate and process data.
 
@@ -51,47 +51,26 @@ Tools are distributed in directories:
 - [Process](process)
 - [Learning](learning)
 
-<details open>
-  <summary>Files layout</summary>
-    Content structure overview with notes
-    <pre>
+Content structure overview with notes 
+<pre>
     ├── PerfSPEC.pdf                   Reference document
     ├── README.md
     ├── about.md
     ├── actions_distribution.pdf       Generated actions distribytion
     ├── collect                        Collect logs scripts 
-    │   ├── audit-policy.yaml
-    │   ├── collect.py
-    │   └── helm-charts.json
     ├── data                           Extracted from compress archive 
-    │   ├── actions-dataset-audit.txt
-    │   ├── actions-logs.log
-    │   ├── actions_distribution.pdf
-    │   ├── main-audit-logs.log
-    │   └── raw-audit-logs.log
     ├── data_sample.tar.xz             Compress archive with 'data'
     ├── imgs
     ├── install.md                     Installation notes
     ├── intro.md
     ├── learning
-    │   └── python
-    │       ├── __pycache__            Ignored in git
-    │       ├── lib_perfspec.py
-    │       ├── model_perfspec.py
-    │       ├── prepare_perfspec.py
-    │       ├── run_perfspec.py
-    │       └── train_perfspec.py
     ├── models                        Extracted from compress archive
-    │   ├── checkpoints
-    │   │   ├── model_at_epoch_175.keras
-    │   │   └── model_at_epoch_185.keras
-    │   ├── history.json
-    │   └── perfSPEC_model.keras
     ├── models_sample.tar.xz          Comperss archive with 'models'
     ├── presentacion.pdf              Presentation slides
     └── raw-audit-logs.log.xz         Main Raw Logs file
-    </pre>
-</details>
+ </pre>   
+
+A [full directory layout](full_content_layout.md) is available.
 
 As some tasks can be used in [Python](https://python.org) or [Rust](https://www.rust-lang.org/) there are or will be directories for each programming languge inside directories tasks.  
 
@@ -101,14 +80,48 @@ Each `task/programming-language` use a common __data__ directory where processin
 
 If you wish to [collect](collect) your own dataset, there are several source files that might help:
 
+- `collect/audit-policy.yaml` is for [Kubernetes](https://kubernetes.io/) event logs capture, other resources are also required: [adminssion controllers](https://kubernetes.io/docs/reference/access-authn-authz/admission-controllers/), etc
 - `collect/collect.py` is a script to trigger the installation and uninstallation of public Helm repositories.
 - `collect/helm-charts.json` is a backup of Helm charts used at the time of the collection.
 
 ## Process data 
 
+raw-audit-logs.log
+main-audit-logs.log
+actions-dataset-audit.txt
 
-## Learning
+actions_distribution.pdf
 
+## Data Models 
+
+> [!CAUTION]  
+> These files are default names and paths, can be changed:
+> - by [settings](learning/python/lib_perfspec.py) modifications
+> - by <u>command-line</u> in running  script mode. Add **--help* for more info 
+
+`models/checkpoints` is where files are stored as part of learning process:
+
+<pre>
+├── checkpoints
+    │   ── model_at_epoch_175.keras
+    └── model_at_epoch_185.keras
+</pre>
+
+`models/perfSPEC_model.keras` is the generated model by default 
+`models/history.json` is model history with stats 
+
+## Learning Notebooks
+
+`learning/python/lib_perfspec.py`  Main library with settings 
+
+`learning/python/prepare_perfspec.py` Prepare data from raw to source for learning models
+
+`learning/python/train_perfspec.py` To train model from data
+`learning/python/run_perfspec.py`   To run/check predictions
+
+`learning/python/model_perfspec.py` To inspect / review generated models
+
+<small>  __ pycache __ is for Python execution,  is  ignored in git tasks.</small>
 
 
 ## Reference