Search
Close this search box.

AI/ML, Data Science

Why Federated models in AI leak secrets

I was at a meeting last week discussing how AI models might be used to support archives forefficiency, effectiveness, etc. while maintaining the requirements for those archives to providereliable and authentic records and maintain confidentiality of relevant record data elements. Someone across the room indicated that they were going to federate models, not records themselves, …

Why Federated models in AI leak secrets Read More »

Train-Test split and Cross-validation: Visual Illustrations & Examples

Creating an optimal model that strikes a balance between underfitting and overfitting requires careful consideration. To assess how well our model performs on new, unseen data, we employ the train-test split technique and cross-validation. Train-Test Split: To evaluate a model’s performance, we split the dataset into a training set (approximately 70-90% of the data) and …

Train-Test split and Cross-validation: Visual Illustrations & Examples Read More »

Enhancing Accessibility and Inclusivity in Education with ChatGPT

Education is the cornerstone of progress, but for it to be truly impactful, it must be accessible and inclusive to all. In recent years, technology has played a pivotal role in transforming the educational landscape, making strides towards greater accessibility and inclusivity. Among these technological advancements stands ChatGPT, an AI-powered tool that not only serves …

Enhancing Accessibility and Inclusivity in Education with ChatGPT Read More »

Non-linear Relationships: When a 0 Pearson Correlation Coefficient Can Be Surprisingly Meaningful

The Pearson correlation coefficient (denoted as “r”) is widely used in statistics to measure the strength and direction of linear relationships between variables, ranging from -1 (perfect negative linear correlation) to +1 (perfect positive linear correlation). A Pearson correlation coefficient of 0 typically implies the absence of a linear relationship between variables. However, the term …

Non-linear Relationships: When a 0 Pearson Correlation Coefficient Can Be Surprisingly Meaningful Read More »

Standard Deviation vs Standard Error: Clearing up the Confusion with Visual Examples

Standard deviation and standard error are two statistical measures that often get confused with each other. While both measures describe the variability in the data, they serve different purposes. Standard deviation measures the spread of the data. It calculates how far the individual data points deviate from the mean of the data set. A low …

Standard Deviation vs Standard Error: Clearing up the Confusion with Visual Examples Read More »

REQUEST DEMO