Google doc's tabs

 

I've just come across this new feature from google docs's tabs. 
This is something similar to tabs we use in browser.

 So we create a document which is aligned towards single topic.
In the same document we can have sub-topics under the single topic.
We can also have sub-sub topic inside :) 

--

Tabs in Google Docs let you create sections within a single document, similar to tabs in a web browser or spreadsheet. Each tab can contain separate content, allowing you to organize related information without switching between different Docs files.

Think of it like this:

• Instead of having 5 separate Docs files for different aspects of a project, you can have 1 Google Doc with 5 tabs, each dedicated to a topic.

   

   Example:

  Let's say we have a AI project with main document name as "AI Assistant for Customer Support"



  We can have tabs as below:
  

  Tab Name	What to Include
  1. Problem Statement	Define the problem you're solving, pain points, target users, and project goals.
  2. Data Collection & Cleaning	Sources of data (chat logs, support tickets), privacy considerations, preprocessing steps.
  3. Model Selection & Training	ML/DL models considered (e.g., BERT, LLMs, custom models), training setups, experiments.
  4. Evaluation & Metrics	Accuracy, F1 score, confusion matrix, user feedback — how you’ll judge model quality.
  5. Deployment Plan	Architecture, inference setup (e.g., REST API), infrastructure (AWS/GCP), latency goals.
  6. UI/UX Design	Interface mockups, chatbot UX, conversation flows.
  7. Risks & Ethical Concerns	Bias, hallucinations, GDPR issues, response safety.
  8. Timeline & Milestones	Sprint plans, deadlines, deliverables.
  9. Team & Roles	Who’s doing what: ML engineer, designer, backend, QA, PM, etc.
  10. References & Tools	Research papers, tech stack, tools used (e.g., Hugging Face, PyTorch, LangChain).

  
  

  This is awesome way to have a organized info.  Thanks Google.
  
  Thanks to ChatGPT for fetching an example.
  

Determine your graphical platform - X11/wayland

 

-- 

Open a terminal and run the command echo $XDG_SESSION_TYPE.

If the output is "x11", then your system is using X11.
If the output is "wayland", then your system is using Wayland.

Most modern systems make use of wayland.
--

Wayland:
A newer, more secure, and potentially more performant display protocol, especially for modern graphics hardware.

X11:
The traditional display server protocol used by many Linux systems, including Ubuntu.

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Education - simulation of concepts

 

Kids education:

https://phet.colorado.edu/

It covers the following:
Physics
Maths and statistics
Chemistry
Earth & Space
Biology

Simulations of concepts.

Check previous boot logs in Linux

==

You can check how many previous boots are recorded using:

journalctl --list-boots

==


journalctl -b     → Shows logs from the current boot

journalctl -b -1  → Shows logs from the previous boot (last boot before the reboot)

journalctl -b  -2 → Shows logs from the boot before the last one, and so on

 ==

To check kernel issues in last boot:

 journalctl -b -k -1

 ==

 

Google Engineering Pracices - Some resources

Some good resources from Google:

--

Code review:
https://google.github.io/eng-practices/review/reviewer/

--

Google Enginerring practices:
https://google.github.io/eng-practices/

--

Go Style Guide:
https://google.github.io/styleguide/go/guide.html

--

Google Python Style Guide:
https://google.github.io/styleguide/pyguide.html

--

Google Summer of Code Guides

https://google.github.io/gsocguides/

--

 

AI/ML courses

AI/ML  courses

https://www.deeplearning.ai/courses

Three modes here - Short course, Course, Specialized

Interesting course I've come across: https://learn.deeplearning.ai/courses/vibe-coding-101-with-replit/

Elephanoid

I stumbled across this post:
https://x.com/Airawat/status/1902001775936405702

and thought of this:

At some point, maybe in another 10-15 years, we should be able to create a robot that resembles an elephant and can perform tasks as effectively as an elephant.
This is similar to a humanoid robot.

All the elephants can remain in their forests.
Wherever elephants are needed, we can make use of an "elephanoid" :)

pip vs pix in python

pip vs pipx: 

 

While both pip and pipx are Python package managers, pip is a general-purpose installer for libraries and apps, while pipx specializes in installing and managing Python applications in isolated environments, making them accessible as command-line tools. [1, 2, 3]

Here's a more detailed breakdown: [1, 3]

• pip (Python Package Installer): [1, 3]
  • Is a general-purpose package installer for both libraries and applications. [1, 3]
  • Installs packages into the global environment or a virtual environment, depending on the user's configuration. [1, 2, 3]
  • Primarily used by developers for managing project dependencies. [2]
  • Can install packages from PyPI (or locally). [3] 
    
• pipx (Install and Run Python Applications in Isolated Environments): [1, 2, 3]
  • Is a specialized tool for installing and managing Python applications as command-line tools. [1, 2, 3]
  • Creates isolated environments for each installed application, preventing dependency conflicts. [1, 2]
  • Installs packages from PyPI (or locally). [3]
  • Makes installed applications accessible as commands in your shell. [1]
  • Is often used by end-users who want to install and run Python-based tools without needing to manage virtual environments or Python installations themselves. [4, 5]
  • pipx relies on pip and venv internally. [3]
  • You can install pipx with pip. [3]

Key Differences and Use Cases:

Feature	pip	pipx
Purpose	General-purpose package installer	Specializes in installing and managing Python applications
Environment Isolation	Installs packages globally or in virtual environments	Creates isolated environments for each application
Target Audience	Developers managing project dependencies	End-users installing and running Python applications
Command-Line Tools	Can install libraries and apps, but doesn't focus on command-line tools	Primarily focuses on installing and managing command-line tools
Example Use Cases	Installing libraries for a Python project, managing project dependencies	Installing command-line tools like black, flake8, or poetry

In essence: [2, 3]

• Use pip when you're developing a Python project and need to install libraries and manage dependencies within a virtual environment. [2, 3]
• Use pipx when you want to install and run Python-based command-line tools as standalone applications, without worrying about virtual environments or dependency conflicts. [1, 2, 3]

Sources:

[1] https://pipx.pypa.io/

[2] https://medium.com/@martia_es/pip-vs-pipx-the-definitive-guide-to-python-package-management-a7039a5c62fa

[3] https://github.com/pypa/pipx/blob/main/docs/comparisons.md

[4] https://stackoverflow.com/questions/78229687/what-is-the-difference-between-pipx-and-using-pip-install-inside-a-virtual-envir

[5] https://software.codidact.com/posts/289427

 

 

datasets

 

Looking for interesting and wide datasets for your projects. 
 

Check here:
https://indiaai.gov.in/datasets/all

Also here: (check for models, datasets, etc.,)
https://aikosha.indiaai.gov.in/

Backup and save your google map's timeline

 

Google map's timeline is no longer available in desktop version.
It is available in Mobile though. ( I don't understand the rationale behind this.
Anyway)

Now, the problem here is, if for some reason your mobile is lost, the entire timeline is lost.

You can take backup of timeline using this link:
https://takeout.google.com/takeout/custom/local_actions,location_history,maps,mymaps 

(Always copy paste link - do not click on link directly)
 

For some reason, you cannot get this link directly from takeout.google.com.
(Why google why?)

• You can schedule to take backup every 2 months. Download link will be sent to your email  id.
• You can take immediate backup too. 
  

Kubernetes playground

 

If you want a sample kubernetes environment where you want to try out some kubectl commands, go here:
https://killercoda.com/playgrounds/scenario/cka

 

It has some limitations but good for a playground :) 

cronjob schedule

 

How to remember cronjob:

 

📝 Mnemonic: "Mini-Hourly-Daily-Monthly-Weekly"

Think of it as:

👉 "Minute - Hour - Day - Month - Week"

🟢 5 stars (* * * * *) means "every minute"

🟢 */X means "every X unit" (e.g., */5 = every 5 minutes)

🟢 0 0 * * * → At midnight every day

🟢 0 12 * * 1-5 → At 12 PM, Monday to Friday

🟢 30 14 1 * * → At 2:30 PM on the 1st of every month

    // 30 14 1 * * => minutes 30, hour 14, day 1 only, every month, irrespective of day.

 

  

Access Windows drive in Linux(fedora)

Access Windows drive in Linux(fedora):

 

# install package necessary for ntfs

dnf install ntfs-3g

 

# create mount point

mkdir -p /mnt/windows/

 

# get the device name

sudo lsblk 

 

# mount drive

mount -t ntfs-3g /dev/<device>  /mnt/windows 

#  To make it permanent across reboots

tail -1 /proc/mounts >> /etc/fstab 

 

Restart shell without exiting

 

--

Restart shell without exiting :

exec $SHELL

--
Now comes some explanation thanks to chatGPT:

The command exec "$SHELL" in Linux is used to replace the current shell with a new instance of the shell.

Here's a breakdown of the components:

1. exec: The exec command in Linux is used to replace the current running process with a new process. When exec is called, the current process is replaced by the new process, and the current shell (or program) is no longer running. This means that after running the command, the original shell or command will not be in the process list anymore.

2. "$SHELL": This refers to the value stored in the SHELL environment variable. The SHELL variable typically holds the path to the user's default shell, such as /bin/bash, /bin/zsh, or /usr/bin/fish, depending on your system configuration.

   • Example: If your default shell is bash, $SHELL would evaluate to /bin/bash.

So, when you run exec "$SHELL", you're telling the system to replace the current shell process with a new instance of the same shell (as defined by the $SHELL variable).

Use cases:

• Restarting the shell: Sometimes, you may want to restart the shell to apply changes to environment variables or configuration files (like .bashrc or .zshrc). Running exec "$SHELL" can be a quick way to do this without logging out and back in.

• Resetting the environment: It can be useful for resetting the shell's environment if you've modified environment variables or paths temporarily and want to start fresh.

Example:

If you are using bash as your default shell, running:

exec "$SHELL"

Would essentially restart the bash shell in the current terminal session, and any changes to the environment or shell configuration would take effect.