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Algebraic Equation Dataset for Machine Learning Introduction This document contains a structured dataset of algebraic equations with their solutions, designed for training machine learning models. The dataset features diverse equation types, from simple linear equations to more complex systems of equations, trigonome...
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Dataset Structure Each entry follows this format: json { "input": "equation as string", "output": "solution", "type": "equation_type" }
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There is no question provided. Please provide a question, and I'll do my best to answer it based on the given document.
Equation Types Linear - Simple first-degree equations (ax + b = c) Quadratic - Second-degree equations (ax² + bx + c = 0) Polynomial - Higher-degree polynomial equations Rational - Equations with fractions containing variables Absolute Value - Equations with absolute value expressions System of Equations - System...
null
There is no question provided. Please provide a question related to the document, and I'll be happy to assist you with a clear and concise answer.
Trigonometric - Equations with trigonometric functions Sample Entries Linear Equations json { "input": "-5x - 10 = 0", "output": "-2", "type": "linear" } json { "input": "8x + 9 = 1", "output": "-1", "type": "linear" } Quadratic Equations json { "input": "x² - 5x + 4 = 0", "output": "[1,4]", "type": "quadratic" }...
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Polynomial Equations json { "input": "x³ - x² - 4x + 4 = 0", "output": "[-2,1,2]", "type": "polynomial" } json { "input": "x³ - x = 0", "output": "[1,0,-1]", "type": "polynomial" } Rational Equations json { "input": "(-4x + 12)/(-x + 3) = 4", "output": "-5", "type": "rational" } json { "input": "(-3x + 27)/(-x + 9...
null
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Absolute Value Equations json { "input": "|-4x + 6| = 4", "output": "[0.5,2.5]", "type": "absolute_value" } json { "input": "|3x + 1| = 4", "output": "[1,-1.6666666666666667]", "type": "absolute_value" } Systems of Equations json { "input": "3x + 5y = 5; 2x - 4y = 10", "output": "{\"x\":-3,\"y\":2}", "type": "syste...
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Exponential Equations json { "input": "10^(-x - 2) = 1", "output": "-2", "type": "exponential" } json { "input": "2^(3x + 1) = 2", "output": "0", "type": "exponential" } Logarithmic Equations json { "input": "log_10(2x + 96) = 2", "output": "2", "type": "logarithmic" } json { "input": "log_3(-3x + 12) = 2", "outpu...
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Trigonometric Equations json { "input": "cos(x + π) = -1", "output": "0", "type": "trigonometric" } json { "input": "sin(x + 0.79) = 0.707", "output": "0", "type": "trigonometric" }
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Linear Equations with Step-by-Step Solutions json { "input": "-4x - 9 = 7", "output": "{\"steps\":[\"Step 1: Start with the original equation: -4x - 9 = 7\",\"Step 2: Move the constant term to the right side: -4x = 7 - 0\",\"Step 3: Simplify the right side: -4x = 7\",\"Step 4: Divide both sides by -4: x = -1.75\",\"St...
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The solution to the linear equation "-4x - 9 = 7" is x = -1.75.
Using This Dataset for ML Training To use this dataset for machine learning model training: Preprocessing: Parse the JSON structure Convert equation strings to appropriate tensor representations Process solutions based on equation type Data Splitting: Split into training (80%), validation (10%), and test (10%) s...
null
There is no question provided in the document. If you would like to ask a question, I'll be happy to help you based on the information provided.
Algebraic Equation Dataset for Machine Learning Introduction This document contains a structured dataset of algebraic equations with their solutions, designed for training machine learning models. The dataset features diverse equation types, from simple linear equations to more complex systems of equations, trigonome...
null
There is no question provided in the document. If you would like to ask a question based on the information in the document, I'll be happy to help.
Dataset Structure Each entry follows this format: json { "input": "equation as string", "output": "solution", "type": "equation_type" }
null
There is no question provided. Please provide a question, and I'll do my best to answer it based on the given document.
Equation Types Linear - Simple first-degree equations (ax + b = c) Quadratic - Second-degree equations (ax² + bx + c = 0) Polynomial - Higher-degree polynomial equations Rational - Equations with fractions containing variables Absolute Value - Equations with absolute value expressions System of Equations - System...
null
There is no question provided in the document. If you would like to ask a question, I'll be happy to help based on the information provided.
Trigonometric - Equations with trigonometric functions Sample Entries Linear Equations json { "input": "-5x - 10 = 0", "output": "-2", "type": "linear" } json { "input": "8x + 9 = 1", "output": "-1", "type": "linear" } Quadratic Equations json { "input": "x² - 5x + 4 = 0", "output": "[1,4]", "type": "quadratic" }...
null
It appears there is no question provided in the document. If you would like to ask a question or provide a specific query related to the document, I'll be happy to assist you.
Polynomial Equations json { "input": "x³ - x² - 4x + 4 = 0", "output": "[-2,1,2]", "type": "polynomial" } json { "input": "x³ - x = 0", "output": "[1,0,-1]", "type": "polynomial" } Rational Equations json { "input": "(-4x + 12)/(-x + 3) = 4", "output": "-5", "type": "rational" } json { "input": "(-3x + 27)/(-x + 9...
null
It appears there is no question provided. If you would like to ask a question based on the document, I'll be happy to help.
Absolute Value Equations json { "input": "|-4x + 6| = 4", "output": "[0.5,2.5]", "type": "absolute_value" } json { "input": "|3x + 1| = 4", "output": "[1,-1.6666666666666667]", "type": "absolute_value" } Systems of Equations json { "input": "3x + 5y = 5; 2x - 4y = 10", "output": "{\"x\":-3,\"y\":2}", "type": "syste...
null
It seems there is no question provided. Please provide a question, and I'll do my best to answer it based on the given document.
Exponential Equations json { "input": "10^(-x - 2) = 1", "output": "-2", "type": "exponential" } json { "input": "2^(3x + 1) = 2", "output": "0", "type": "exponential" } Logarithmic Equations json { "input": "log_10(2x + 96) = 2", "output": "2", "type": "logarithmic" } json { "input": "log_3(-3x + 12) = 2", "outpu...
null
It appears there is no question provided. If you could please provide a question related to the document, I'll be happy to assist you with a clear and concise answer.
Trigonometric Equations json { "input": "cos(x + π) = -1", "output": "0", "type": "trigonometric" } json { "input": "sin(x + 0.79) = 0.707", "output": "0", "type": "trigonometric" }
null
There is no question provided in the prompt. If you would like to ask a question, I'll be happy to help based on the information in the document.
Linear Equations with Step-by-Step Solutions json { "input": "-4x - 9 = 7", "output": "{\"steps\":[\"Step 1: Start with the original equation: -4x - 9 = 7\",\"Step 2: Move the constant term to the right side: -4x = 7 - 0\",\"Step 3: Simplify the right side: -4x = 7\",\"Step 4: Divide both sides by -4: x = -1.75\",\"St...
null
The solution to the linear equation "-4x - 9 = 7" is x = -1.75.
Using This Dataset for ML Training To use this dataset for machine learning model training: Preprocessing: Parse the JSON structure Convert equation strings to appropriate tensor representations Process solutions based on equation type Data Splitting: Split into training (80%), validation (10%), and test (10%) s...
null
There is no question provided in the document. If you would like to ask a question based on the information in the document, I'll be happy to help.

YAML Metadata Warning:The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

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Dataset Card for my-distiset-1129e648

This dataset has been created with distilabel.

Dataset Summary

This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:

distilabel pipeline run --config "https://huggingface.co/datasets/BarefootMikeOfHorme/my-distiset-1129e648/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/BarefootMikeOfHorme/my-distiset-1129e648/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default
{
    "context": "Algebraic Equation Dataset for Machine Learning\n\nIntroduction\n\nThis document contains a structured dataset of algebraic equations with their solutions, designed for training machine learning models. The dataset features diverse equation types, from simple linear equations to more complex systems of equations, trigonometric, exponential, and logarithmic equations.",
    "question": null,
    "response": "There is no question provided in the document. If you would like to ask a question, I\u0027ll be happy to help you find an answer based on the information provided."
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("BarefootMikeOfHorme/my-distiset-1129e648", "default")

Or simply as it follows, since there's only one configuration and is named default:

from datasets import load_dataset

ds = load_dataset("BarefootMikeOfHorme/my-distiset-1129e648")
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