An example of performing simple linear regression using train-test split where the process is as follows, 1. Generate a synthetic dataset: 2. Split the dataset: We use train_test_split to divide the data into training and… Simple linear regression using train-test split in Python & R
Reviewers are not required to read supplementary materials, but many do. Therefore, making your proof easy to read is important. General Guidelines: Example: Theorem 1: Let and be real numbers. If , then . The… How to Write a Proof in a paper
Dosage Optimization: Pharmacologists use derivatives to find the optimal drug dosage that maximizes therapeutic effects while minimizing side effects. The concentration of the drug in the bloodstream is modeled as a function of time, and… Example of using derivatives to find optimal drug dosage
Optimization of Material Usage: Engineers use derivatives to minimize the cost of materials while maintaining structural integrity. For example, determining the optimal dimensions of a container to minimize surface area for a given volume. Example:… Example of using derivatives to optimize the material cost
Problem 2: Find the minimum distance from the point (2, 3) to the line . Solution: More examples:
Detailed information can be found in Combining datasets to improve model fitting or its presentation slide. Summary: The key points of the paper titled “Combining Datasets to Improve Model Fitting” are as follows: Problem and… Combining datasets to increase sample size
Supplementary contents for section “Calculus can hurt” in the KSML app: Limit: Derivatives Integral
Expectation Maximization (EM) is an iterative algorithm used for finding maximum likelihood estimates of parameters in statistical models, particularly when the model involves latent variables (variables that are not directly observed). The algorithm is commonly… Expectation Maximization (EM) & implementation
Handling noisy data is a crucial step in data preprocessing and analysis. In general, here are some common approaches to manage noisy data: 1. Data Cleaning 2. Data Transformation 3. Statistical Techniques 4. Machine Learning… A comic guide to denoising noisy data
After you introduce the motivation of your work, it’s time to write a paragraph detailing the contribution of your work for a paper. In that paragraph, consider the following structure and key elements: Significance and… Writing the paragraph detailing the contribution of your paper