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- Linear Algebra and Affine Projective Geometry11 min
Vector spaces form the foundation of linear algebra. They are sets of vectors that can be added together and multiplied by scalars. Let's explore a simple...
- Linear Algebra for AI and ML Inverse and Determinants in Python12 min
Linear algebra forms the backbone of many machine learning algorithms and AI techniques. It provides the mathematical foundation for understanding and...
- Linear Algebra Fundamentals for Quant Finance and ML10 min
Linear algebra operations in quantitative finance start with vectors representing asset returns, prices, or risk factors. NumPy provides efficient tools for...
- Matrix Factorization and Tensor Methods9 min
NMF is a powerful technique for decomposing a nonnegative matrix V into two nonnegative matrices W and H, such that V ≈ WH. This method is widely used in...
- Matrix Operations in Python4 min
Matrices are two-dimensional arrays that represent a collection of numbers arranged in rows and columns. Python provides several ways to work with matrices...
- Matrix-based Rank Adaptation (MoRA) in Python6 min
Introduction to Matrix-based Rank Adaptation (MoRA)
- Methods for Matrix Multiplication in Python with NumPy5 min
Matrix multiplication is a fundamental operation in linear algebra and has numerous applications in various fields. This presentation will explore three...
- Negative Binomial Regression for Predicting Video Views10 min
Negative Binomial Regression is a statistical model used for count data with overdispersion. It's an extension of Poisson regression that allows for greater...
- Poisson Regression for Modeling Count Data7 min
The Poisson distribution models the probability of events occurring in fixed intervals of time or space. It's particularly useful for count data where events...
- Power of Matrix Theory using Python7 min
Matrix theory is a fundamental branch of mathematics with wide-ranging applications in various fields. It provides a powerful framework for solving complex...
- Regression Analysis: Understanding R-Squared vs. Adjusted R-Squared in Python9 min
Regression analysis is a powerful statistical method used to model relationships between variables. It's widely applied in various fields, from economics to...
- Scalar, Vector, Matrix, and Tensor The Foundations of Data Science in Python10 min
These fundamental mathematical structures form the backbone of modern data science, enabling complex computations and representations in Python. We'll...
- Understanding R-squared and Adjusted R-squared in Regression Models12 min
R-squared (R²) and adjusted R-squared are statistical measures used to evaluate the goodness of fit of regression models. They provide insights into how well...
- Understanding the Range of R-squared in Regression9 min
R-squared, also known as the coefficient of determination, measures the proportion of variance in the dependent variable explained by independent variables...
- Understanding Vectors in Linear Algebra with Python11 min
Vectors are fundamental elements in linear algebra, representing quantities with both magnitude and direction. They form the backbone of many mathematical...
- Variance Inflation Factor (VIF) and Regression Diagnostics in Python6 min
VIF and regression diagnostics are essential tools in statistical analysis, helping to identify and address multicollinearity and other issues in linear...
- Why Ordinary Least Squares is an Unbiased Estimator3 min
Python's type system provides flexible and dynamic variable handling. Variables are containers that store data, and their type is determined automatically...
- Beginner's Guide to Real Analysis in Python6 min
Mathematical real analysis topics in Python at a beginner level, with each slide containing a title, brief description, and example
- Beginners Guide to Analysis I in Python:2 min
- Bernoulli Distribution Explained with Python8 min
The Bernoulli distribution is a discrete probability distribution for a binary random variable. It models scenarios with two possible outcomes, often...
- Bernoulli Distribution Probability Modeling Explained10 min
The Bernoulli distribution models binary outcomes where a random variable X can take only two possible values: success (1) with probability p or failure (0)...
- Converting Normal to Standard Normal Distributions in Python8 min
The process of transforming a normal distribution to a standard normal distribution is a fundamental technique in statistics and data analysis. This...
- Correlation Pitfalls Avoiding Misleading Statistics11 min
Correlation coefficients can be deceptive when analyzing relationships between variables. While a correlation value provides a single numeric measure of...
- Discrete Distributions Python Cheat Sheet6 min
Discrete distributions are probability distributions that describe random variables that can only take on specific, distinct values. These distributions are...
- Discrete Probability Distributions in Python7 min
Discrete distributions are probability distributions that describe random variables with a finite or countably infinite set of possible values. They are...
- Empirical Rule and Normal Distribution in Python9 min
The Empirical Rule, also known as the 68-95-99.7 rule, is a fundamental concept in statistics that describes the distribution of data in a normal...
- Essentials of Probability and Statistics5 min
Probability is the branch of mathematics that deals with the likelihood of events occurring. It forms the foundation for statistical analysis and...
- Explaining Normal Distribution in Data Science10 min
The Normal Distribution, also known as the Gaussian distribution, is a symmetrical, bell-shaped curve that represents the probability distribution of many...
- Exploring Conditional Probability with Python12 min
Conditional probability is a fundamental concept in statistics that allows us to calculate the likelihood of an event occurring given that another event has...
- Gaussian Filters for Smoothing Time Series Data6 min
The Gaussian filter is a fundamental smoothing technique that applies a weighted average using the normal distribution. It's particularly effective for...