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Linear Regression – Assumption – 2 (What Is A Singular Matrix?)
What Is A Singular Matrix? Table Of Contents: What Is A Singular Matrix? (1) What Is A Singular Matrix? A singular matrix is a square matrix that does not have an inverse. This happens when its determinant is equal to zero. In other words, a matrix is singular if it is not full rank, meaning some of its rows or columns are linearly dependent, and they can be expressed as a linear combination of the others. (2) Properties Of A Singular Matrix. (3) Example Of A Singular Matrix. Example-1: Example-2:
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Linear Regression – Assumption – 2 (What Is Standard Error ?)
What Is Standard Error? Table Of Contents: What Is Standard Error? Why Standard Error Is Called Standard ? Factors Affecting Standard Error. Theoretical Range Of Standard Error. Key Concepts In Standard Error. Types Of Standard Error. Mathematical Example Of Standard Error. Why Standard Error Matters? Practical Example Of Standard Error. Linear Regression Coefficients Standard Error. (1) What Is Standard Error? The Standard Error (SE) is a measure of the variability or uncertainty of a statistic, such as a mean, proportion, or regression coefficient, when calculated from a sample. It quantifies how much a sample statistic (e.g., sample mean, xˉbar{x}xˉ) is
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Outlier Handling Techniques.
Outlier Detection Techniques Table Of Contents: What Is An Outlier ? Characteristics Of An Outlier. Causes Of Outlier. Why Handle Outliers? Outlier Handling Techniques. Python Examples. (1) What Is An Outlier? An outlier is a data point that significantly deviates from the rest of the dataset. It is unusually large or small compared to other values and may indicate variability, errors, or rare events. (2) Example Of An Outlier. Data Set: 150, 160, 162, 158, 170, 165, 175, 169, 180, 300. In this example, the height 300 cm is an outlier because it is much higher than the other values,
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Data Cleaning Strategies.
Data Cleaning Strategies Table Of Contents: What Is Data Cleaning? Handling Missing Data. Handling Outliers. Removing Duplicate Data. Standardizing Column Names. Standardizing Data Formats Correct Data Types. Feature Selection. Feature Engineering. Addressing Class Imbalance. Dealing With Multicollinearity. Encoding Categorical Variables. Data Normalization & Standardization. Handling Text Data. Handling Time Series Data. Saving the Cleaned Data. (1) What Is Data Cleaning? In simple terms, data cleaning is the process of fixing or removing incorrect, incomplete, or irrelevant data from a dataset. It ensures that the data is accurate, consistent, and ready for analysis or use in a machine learning model. (2)
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What Is Albumentations Python Library?
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What Is Token ID and Attention Mask In NLP?
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What Is Temperature Hyperparameter?
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What Is Number Of Workers In Deep Learning?
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What Is Batch Size In Deep Learning?
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What Is Patience In Deep Learning?
