Mastering Prompt Engineering: Ensuring Precise Outputs with LLM Models
As artificial intelligence continues to expand, the importance of effectively communicating with large language models (LLMs) is crucial.
Data-Led Customer Lifecycle Management: A Practical Solution to Increase Conversion and Retention
Market study notes that customer churn costs US provider a staggering $168 Billion per year and a just a 5% increase in retention can boost profitability by up to 75%. In addition, a customer’s likelihood to make another purchase increases by 2.3X after their 3rd purchase indicating the importance.
"EDA and Beyond: Understanding, Detecting, and Interpreting Outliers"
Assume that everyone is dressed casually at a party, except for one person who is wearing a superhero outfit. You notice that person right away since they do not fit in the crowd. This superhuman visitor is referred to as an outlier in data analysis.
Supercharge Your AI Agents: The Power of Evaluations
As AI agents become increasingly prevalent in software applications, it's essential to ensure they're performing optimally. But how do you measure their success?
Optimizing Large Language Models: Techniques and Future Directions for Efficiency
Ever since OpenAI introduced ChatGPT UI in November 2022, the way we interact, process and consume information has changed drastically. It was science fiction to have a long and meaningful conversation with a machine until this point.
Making AI transparent- The What, Why and How of Explainable AI
In 2015, one of the largest e-commerce companies built an automated hiring tool to review and filter resumes based on skill sets and job descriptions. However, this project had to be halted after it was noticed that the hiring tool showed significant racial bias and systematically discriminated.
Insights from the Data Science Salon’s AI & Machine Learning Conference in San Francisco
Have you ever had one of those days where it feels like you time-traveled into the future? That’s exactly how I felt when I attended the Data Science Salon’s conference on “Using AI & Machine Learning in the Enterprise” at Google’s San Francisco headquarters.
Tackling burnout with Large Language Models
Industry burnout is interlinked with cultural, individual, physical, or emotional exhaustion, and social factors, the resolution of which requires the technology-driven trends in the workplace and the technologies such as work pattern monitoring and Artificial Intelligence that can deal with large.
Data Privacy Challenges with Large Language Models
Large Language Models (LLMs) have rapidly evolved, building on decades of research and advances in computing power and data availability. Most LLMs consist of billions of parameters; trained on vast amounts of diverse datasets. LLMs generate highly contextual and personalized outputs. This.
Introduction: From Simple to Multiple Linear Regression
In our previous post, we introduced Linear Regression, a fundamental technique used to predict outcomes based on a single factor—such as estimating house prices based on square footage. We also discussed essential performance metrics like Mean Squared Error (MSE) and R-squared, which help assess.
