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rohitinu6 / Stock-Price-Prediction

This project focuses on predicting the stock prices of "The State Bank Of India" using machine learning Regression algorithms.
MIT License
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[FEATURE] Add Intel-Specific Optimization Section to README.md #174

Open priyansh985 opened 2 days ago

priyansh985 commented 2 days ago

Is this a unique feature?

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.

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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 commented 1 day ago

@jvedsaqib @Mayureshd-18 Please go through this

priyansh985 commented 1 day ago

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