[FEATURE] Add Intel-Specific Optimization Section to README.md

[priyansh985]

Is this a unique feature?

• I have checked "open" AND "closed" issues and this is not a duplicate

Is your feature request related to a problem/unavailable functionality? Please describe.

The README.md currently lacks details on how users can optimize the project for Intel CPUs. Intel offers specific tools, such as the Intel AI Analytics Toolkit, which can significantly enhance performance, especially for libraries like pandas and scikit-learn. Without clear documentation, users may not be able to fully utilize the potential of their Intel hardware.

Proposed Solution

I propose adding a subsection in the README.md titled "Intel-Specific Optimizations." This section would:

1. Provide instructions on installing and configuring the Intel AI Analytics Toolkit for optimizing data science workflows.
2. Include examples demonstrating how to switch to Intel-optimized versions of pandas and scikit-learn.
3. Show performance comparisons highlighting the benefits of using Intel-specific libraries.
4. Provide code snippets that allow users to easily integrate these optimizations into their existing workflows.

This contribution is part of my efforts for Hacktoberfest and GSSoC 2024, aiming to improve the project's performance for users on Intel hardware.

Screenshots

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Do you want to work on this issue?

Yes

If "yes" to above, please explain how you would technically implement this (issue will not be assigned if this is skipped)

To implement the Intel-specific optimization section, I will:

Research Intel AI Analytics Toolkit:

Explore how the Intel AI Analytics Toolkit optimizes libraries like pandas and scikit-learn for Intel CPUs.
Identify the best practices for installing and configuring the toolkit.
Write Detailed Instructions:

Provide a step-by-step guide on installing the Intel AI Analytics Toolkit.
Demonstrate how to switch from standard pandas and scikit-learn to their Intel-optimized versions (e.g., using modin.pandas for pandas).
Include Code Snippets and Examples:

Add code examples showing how users can modify their current setup to use Intel-optimized libraries. For example:
python
Copy code
import modin.pandas as pd # Instead of regular pandas
Provide similar instructions for using Intel-optimized scikit-learn.
Performance Benchmarks:

If possible, include performance benchmarks showing the improvements in speed when using Intel-optimized libraries compared to the standard ones.
Update README.md:

Add this content under a new section called "Intel-Specific Optimizations" in the README.md.
Currently, I am focusing on implementing Intel-specific optimizations only. However, in the future, when I implement optimizations for other hardware platforms (e.g., NVIDIA, AMD), I will surely update the README.md to include those changes as well.

[rohitinu6]

@jvedsaqib @Mayureshd-18 Please go through this

[priyansh985]

@jvedsaqib and @Mayureshd-18 kindly review the issue and assign it to me

[jvedsaqib]

@priyansh985 can you just make a section attached with an hyperlink that will redirect us to another markdown file where Intel Specific info is present

[priyansh985]

@jvedsaqib sure and thanks and I am also working on other optimisation technologies as well to fully optimize the code can you please add labels like level 2 and gssoc and hacktoberfest

[Mayureshd-18]

@priyansh985 Assigned you! Please create a PR for the same.

[priyansh985]

@Mayureshd-18 thanks sure ill do it

[github-actions]

✅ This issue has been successfully closed. Thank you for your contribution and helping us improve the project! If you have any more ideas or run into other issues, feel free to open a new one. Happy coding! 🚀