Increasing the speed of analysis is a benefit of machine learning for solving business problems. Machine learning is a branch of artificial intelligence that involves creating systems that can learn from data and make predictions or decisions. Machine learning can help increase the speed of analysis by automating and optimizing various tasks, such as data processing, feature extraction, model training, model evaluation, or model deployment. Machine learning can also help handle large and complex data sets that may be difficult or impractical to analyze manually or with traditional methods.

This SQL query provides the Directors' Firstname, Lastname, the name of their departments, and the average employee's salary by joining the three tables using the appropriate join types and conditions. The RIGHT JOIN between Employee_Table and Department_Table ensures that all departments are included in the result, even if they have no employees. The INNER JOIN between Department_Table and Directorjable ensures that only departments with directors are included in the result. The GROUP BY clause groups the result by the directors' names and departments' names, and calculates the average salary for each group using the AVG function. Reference: SQL Joins - W3Schools, SQL GROUP BY Statement - W3Schools

Latency is the time delay between a request and a response. Latency can affect the performance and user experience of an application, especially when real-time or near-real-time responses are required. Deploying a deep learning model as an embedded model on edge devices can reduce latency, as the model can run locally on the device without relying on network connectivity or cloud servers. Edge devices are devices that are located at the edge of a network, such as smartphones, tablets, laptops, sensors, cameras, or drones.

Skip-gram and TF-IDF are both text vectorization methods that convert text into numerical feature vectors. Skip-gram is a prediction-based word embedding method that learns vector representations of words from their contexts in a large corpus of text. TF-IDF is a frequency-based word weighting method that assigns scores to words based on their importance in a document and in a corpus of documents. Reference:Text Vectorization and Word Embedding | Guide to Master NLP (Part 5),What Is Text Vectorization? Everything You Need to Know - deepset

Anomaly detection is an unsupervised learning technique that identifies outliers or abnormal patterns in data, which can be useful for fraud detection. Anomaly detection algorithms can learn the normal behavior of transactions and flag the ones that deviate significantly from the norm, indicating possible fraud.