change readme

README.md

@@ -1,4 +1,4 @@
-# Cookiecutter Cookiekaker Data Science Template inspired by @vasinkd and @drivendata
+# Cookiekaker Cookiecutter Data Science Template inspired by @vasinkd and @drivendata
 
 _A not quite logical, nad unreasonably standardized, but flexible project structure for doing and sharing data science work at certain motivation and place._
 
@@ -26,20 +26,9 @@ $ cookiecutter https://github.com/metya/cookiekaker
 ```
 
 __Features:__
-- May choose python3.5, python3.6, python3.7, python3.8
-
-
 - Creation of virtual envronment is limited to virtualenv.
 - Creation of virtual envronment also sets up git vcs and dvc vcs and pre-commit hooks
-- Project library renamed from src to project_name which lets you use the created library on your machine from anythere
-- Added pipeline folder to store all dvc pipelines there
-- Added data/features folder
-- Added settings.py to illustrate how to use .env file
-- Added an empty noteboook "1.0-{{cookiecutter.author_name}}-dvc-pipeline.ipynb" to store all dvc pipelines creation commands and to illustrate that numeration of notebooks is a good idea
-- Cleared make_dataset.py since I find it too restrictive and confusing
-- Removed aws sync functions
-- Removed data folder from .gitignore since dvc version control takes care of .gitignore
-- Removed tox.ini since .pre-commit.yaml is enough for me
+- Good sturcture of folders from SOTA projects
 
 ### The resulting directory structure
 ------------
@@ -54,8 +43,6 @@ The directory structure of your new project looks like this:
 │   ├── external       <- Data from third party sources.
 │   ├── interim        <- Intermediate data that has been transformed.
 │   ├── processed      <- The final, canonical data sets for modeling.
-│   ├── features       <- Features may be stored here
-│   ├── inference      <- Inference stages may be stored here
 │   └── raw            <- The original, immutable data dump.
 │
 ├── docs               <- A default Sphinx project; see sphinx-doc.org for details
@@ -66,8 +53,6 @@ The directory structure of your new project looks like this:
 │                         the creator's initials, and a short `-` delimited description, e.g.
 │                         `1.0-jqp-initial-data-exploration`.
 │
-├── references         <- Data dictionaries, manuals, and all other explanatory materials.
-│
 ├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
 │   └── figures        <- Generated graphics and figures to be used in reporting
 │
@@ -78,17 +63,11 @@ The directory structure of your new project looks like this:
 │
 ├── __init__.py
 │
-└── <project_name>     <- Source code for use in this project.
+└── nets     <- Source code for nets and other stuff use in this project.
     ├── __init__.py    <- Makes {{cookiecutter.repo_name}} a Python module
     │    
     ├── settings.py <- illustrates how to use .env file
     │
-    ├── data           <- Scripts to download or generate data
-    │   └── make_dataset.py
-    │
-    ├── features       <- Scripts to turn raw data into features for modeling
-    │   └── featurize.py
-    │
     └── models         <- Scripts to train models and then use trained models to make
         │                 predictions
         └── train.py