Added boilerplate for time series data

HOWTO.md

@@ -1,34 +1,34 @@
-<h1 align = "center">HOWTO</h1>
-
-<div align = "justify">
-
-The template provides a minimal approach for getting started with an AI/ML project, and has hardly any dependencies required. However, the [`notebooks/BOILERPLATE.ipynb`](notebooks/BOILERPLATE.ipynb) provides popular import and its configurations (like `pandas`, `numpy`, `scikit-learn` and `tensorflow`). A high level directory overview is as follows:
-
-```
-├───config          : store all configuration files
-│
-├───data            : responsible for all data handling, or contains raw data
-│   └───processed   : contains processed data (like combined/normalized dataframes, tables, etc.)
-│
-├───logs            : repository to contain log files, can also be saved in `/path/to/directory`
-│
-├───notebooks       : contains boilerplate notebook for EDA and quick data understanding/explanations
-│
-├───output          : directory responsible for all output files
-│   ├───images      : save output images
-│   └───savedmodels : save trained model files
-│
-├───src             : source directory
-│   ├───agents      : define agents for any rnn application
-│   ├───engine      : provides a suit of machine learning analytic functions
-│   └───models      : directory containing model definations
-│
-├───static          : other important/useful resources required in the project
-│   ├───fonts       : store additional fonts, maybe used in documentations
-│   ├───images      : store explanatory images
-│   └───logo        : setup a project logo
-│
-└───utilities       : utilities directory containing functions and/or submodules
-```
-
-</div>
+<h1 align = "center">HOWTO</h1>
+
+<div align = "justify">
+
+The template provides a minimal approach for getting started with an AI/ML project, and has hardly any dependencies required. However, the [`notebooks/BOILERPLATE.ipynb`](notebooks/BOILERPLATE.ipynb) provides popular import and its configurations (like `pandas`, `numpy`, `scikit-learn` and `tensorflow`). A high level directory overview is as follows:
+
+```
+├───config          : store all configuration files
+│
+├───data            : responsible for all data handling, or contains raw data
+│   └───processed   : contains processed data (like combined/normalized dataframes, tables, etc.)
+│
+├───logs            : repository to contain log files, can also be saved in `/path/to/directory`
+│
+├───notebooks       : contains boilerplate notebook for EDA and quick data understanding/explanations
+│
+├───output          : directory responsible for all output files
+│   ├───images      : save output images
+│   └───savedmodels : save trained model files
+│
+├───src             : source directory
+│   ├───agents      : define agents for any rnn application
+│   ├───engine      : provides a suit of machine learning analytic functions
+│   └───models      : directory containing model definations
+│
+├───static          : other important/useful resources required in the project
+│   ├───fonts       : store additional fonts, maybe used in documentations
+│   ├───images      : store explanatory images
+│   └───logo        : setup a project logo
+│
+└───utilities       : utilities directory containing functions and/or submodules
+```
+
+</div>

notebooks/BOILERPLATE.ipynb

@@ -380,7 +380,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.10.9"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,