Who this book is for
This book is highly recommended for Entry Level Database Administrators, as it provides a suitable starting point for their journey. It assumes some prior knowledge of Database Management Systems (DBMS) to ensure a smooth learning experience. Additionally, senior or experienced developers will find value in this book, particularly in gaining insights into the latest features incorporated in the most recent version of the DB, enhancing their understanding and proficiency in its use.

Description

Creating data models has never been straightforward. This book demonstrates how to formulate a complete business analytics model that combines several data sources, executes numerous computations, and scales across hundreds of BI users.To begin, you'll learn about the Microsoft Power BI ecosystem by downloading the Power BI desktop and exploring all of its features and capabilities. 

Power BI is a powerful Business Intelligence tool developed by Microsoft that helps you connect, analyze, and visualize data from a wide range of sources. If you are looking to gain a solid understanding of Power BI, then this book is for you.

Key Features
● Gain practical experience with cyber threat intelligence by using the book's lab sections.
● Improve your CTI skills by designing a threat intelligence system.
● Assisting you in bridging the gap between cybersecurity teams.
● Developing your knowledge of Cyber Intelligence tools and how to choose them.

Key Features
● Prime focus on feature-engineering, model-exploration & optimization, dataops, ML pipeline, and scaling ML API.
● A step-by-step approach to cover every data science task with utmost efficiency and highest performance.
● Access to advanced data engineering and ML tools like AirFlow, MLflow, and ensemble techniques.

The book will be divided into chapters based on primary Machine Learning topics like Classification, Regression, Clustering, Deep Learning, Text Mining, etc. The book will also explain different techniques of putting Machine Learning models into production-grade systems using Big Data or Non-Big Data flavors and standards for exporting models.

 Prateek has implemented various end-to-end Data Science projects for fishing, winery, and ecommerce clients. His implemented object detection and recognition models and product recommendation engines have solved many business problems of various clients.

Key Features
● Exposure to well-known RL techniques, including Monte-Carlo, Deep Q-Learning, Policy Gradient, and Actor-Critical.

● Hands-on experience with TensorFlow and PyTorch on Reinforcement Learning projects.
● Everything is concise, up-to-date, and visually explained with simplified mathematics.

A Guide to Enter the Journey of a Digital Forensic Investigator Key Features ● Provides hands-on training in a forensics lab, allowing learners to conduct their investigations and analysis. ● Covers a wide range of forensics topics such as web, email, RAM, and mobile devices. ● Establishes a solid groundwork in digital forensics basics including evidence-gathering tools and methods. 

Key Features
● Access to industry-recognized AI methodology and deep learning mathematics with simple-to-understand examples.
● Encompasses MDP Modeling, the Bellman Equation, Auto-regressive Models, BERT, and Transformers.
● Detailed, line-by-line diagrams of algorithms, and the mathematical computations they perform.