We take a grounded look at the applications of AI in the banking industry: credit risk modeling, fraud detection, customer churn, and customer service bots. Discussing the challenges faced in these areas reveals why the progress of AI in this industry may be slowed.

Explore how text embeddings work, their evolution, key applications, and top models, providing essential insights for both aspiring & junior data practitioners.

Explore the key differences between two popular business intelligence tools: Looker Studio and Power BI. Determine which one is best fit for your needs.

Explore the key differences between Power BI and Alteryx in user interface, integration, cost, and learning curve to determine the best fit for your needs.

The Artificial Intelligence (AI) development surge has created a notable increase in computing demands, driving the necessity for robust hardware solutions. Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs) have emerged as pivotal technologies in addressing these demands.

Codestral is Mistral AI's first open-weight generative AI model designed for code generation tasks, automating code completion, generation, and testing across multiple languages.

Reinforcement learning from AI feedback (RLAIF) leverages AI models to provide feedback during LLM training, enhancing performance and scalability.

Learn how to ace your technical interview.

AWS Lambda is a serverless compute service and an increasingly common subject in technical interviews. Whether you're new to cloud computing or a seasoned pro, understanding AWS Lambda is essential.

Learn about transfer learning, fine-tuning, and their foundational roles in machine learning and generative AI.

Comparing Flink vs. Spark, two open-source frameworks at the forefront of batch and stream processing.

The main types of databases include relational databases for structured data, NoSQL databases for flexibility, cloud databases for remote access, and vector databases for machine learning applications.