Take a look at our COM062000 books. Shulph carries a great selection of COM062000 books, and we are always adding more.
A step-by-step that will help you build Microservices architecture using Django and Python Key Features Understand in-depth the fundamentals of Microservices Learn how to create and use Django APIs Use web technology such as Nginx, Gunicorn, UWSGI, and Postgresql to deploy a Django project Description Microservices architectures solve the multiple problems of software architecture. Django is a full-stack development framework, written in python. This book includes everything necessary for web application development, from the user views to the information storage: model, persistence, relationships, controllers, forms, validations, rest API and a very useful back office. Furthermore, the book will show how to build production-ready microservices. It will help you create restful APIs and get familiar with Redis and Celery. Towards the end, the book will show how to secure these services and deploy these microservices using Django. Lastly, it will show how to scale our services. What will you learn Understand the basics of Python, Django, and Microservices Learn how to deploy Microservices with Django Get familiar with Microservices Architecture - Designing, Principles, and Requirements Implement Asynchronous task, JWT API Authentication and AWS Serverless with Microservice architecture Who this book is for This book is for those beginners who want to make their careers in software development. It starts from the basics of python and Django, takes the reader to the Microservices architecture. Table of Contents 1. Basic of Python 2. Major Pillars of OOPS with Python 3. Getting Started with Django 4. API Development with Django 5. Database Modeling with Django
Plan, build, deploy, and monitor data solutions on Azure Key Features -Work with PostgreSQL, MySQL, and CosmosDB databases on Microsoft Azure. -Work with whole data architecture, leverage Azure Storage, Azure Synapse, and Azure Data Lake. -Data integration strategies with Azure Data Factory and Data Bricks. Description 'Hands-On Azure Data Platform' helps readers get a fundamental understanding of the Database, Data Warehouse, and Data Lake and their management on the Azure Data Platform. The book describes how to work efficiently with Relational and Non-Relational Databases, Azure Synapse Analytics, and Azure Data Lake. The readers will use Azure Databricks and Azure Data Factory to experience data processing and transformation. The book delves deeply into topics like continuous integration, continuous delivery, and the use of Azure DevOps. The book focuses on the integration of Azure DevOps with CI/CD pipelines for data ops solutions. The book teaches readers how to migrate data from an on-premises system or another cloud service provider to Azure. After reading the book, readers will develop end-to-end data solutions using the Azure data platform. Additionally, data engineers and ETL developers can streamline their ETL operations using various efficient Azure services. What you will learn -In-depth knowledge of the principles of the data warehouse and the data lake. -Acquaint yourself with Azure Storage Files, Blobs, and Queues. -Create relational databases on the Azure platform using SQL, PostgreSQL, and MySQL. -With Cosmos DB, you can create extremely scalable databases and data warehouses. -Utilize Azure Databricks and Data Factory to develop data integration solutions. Who this book is for This book is designed for big data engineers, data architects, and cloud engineers who want to understand how to use the Azure Data Platform to build enterprise-grade solutions. Learning about databases and the Azure Data Platform would be helpful but not necessary. Table of Contents 1. Getting Started with the Azure Data Platform 2. Working with Relational Databases on Azure 3. Working with Azure Synapse Analytics 4. Working with Azure Data Lake 5. Working with Azure Cosmos DB 6. Working with Azure Databricks 7. Working with Azure Data Factory 8. DevOps with the Azure Data Platform 9. Planning and Migrating On-Premises Azure Workloads to the Azure Data platform 10. Design and Implement Data Solutions on Azure
Get familiar and work with the basic and advanced Modeling types in Verilog HDL Key Features Learn about the step-wise process to use Verilog design tools such as Xilinx, Vivado, Cadence NC-SIM Explore the various types of HDL and its need Learn Verilog HDL modeling types using examples Learn advanced concept such as UDP, Switch level modeling Learn about FPGA based prototyping of the digital system Description Hardware Description Language (HDL) allows analysis and simulation of digital logic and circuits. The HDL is an integral part of the EDA (electronic design automation) tool for PLDs, microprocessors, and ASICs. So, HDL is used to describe a Digital System. The combinational and sequential logic circuits can be described easily using HDL. Verilog HDL, standardized as IEEE 1364, is a hardware description language used to model electronic systems. This book is a comprehensive guide about the digital system and its design using various VLSI design tools as well as Verilog HDL. The step-wise procedure to use various VLSI tools such as Xilinx, Vivado, Cadence NC-SIM, is covered in this book. It also explains the advanced concept such as User Define Primitives (UDP), switch level modeling, reconfigurable computing, etc. Finally, this book ends with FPGA based prototyping of the digital system. By the end of this book, you will understand everything related to digital system design. What will you learn Implement Adder, Subtractor, Adder-Cum-Subtractor using Verilog HDL Explore the various Modeling styles in Verilog HDL Implement Switch level modeling using Verilog HDL Get familiar with advanced modeling techniques in Verilog HDL Get to know more about FPGA based prototyping using Verilog HDL Who this book is for Anyone interested in Electronics and VLSI design and want to learn Digital System Design with Verilog HDL will find this book useful. IC developers can also use this book as a quick reference for Verilog HDL fundamentals & features. Table of Contents 1. An Introduction to VLSI Design Tools 2. Need of Hardware Description Language (HDL) 3. Logic Gate Implementation in Verilog HDL 4. Adder-Subtractor Implementation Using Verilog HDL 5. Multiplexer/Demultiplexer Implementation in Verilog HDL 6. Encoder/Decoder Implementation Using Verilog HDL 7. Magnitude Comparator Implementation Using Verilog HDL 8. Flip-Flop Implementation Using Verilog HDL 9. Shift Registers Implementation Using Verilog HDL 10. Counter Implementation Using Verilog HDL 11. Shift Register Counter Implementation Using Verilog HDL 12. Advanced Modeling Techniques 13. Switch Level Modeling 14. FPGA Prototyping in Verilog HDL About the Author Dr. Cherry Bhargava is working as an associate professor and head, VLSI domain, School of Electrical and Electronics Engineering at Lovely Professional University, Punjab, India. She has more than 14 years of teaching and research experience. She is Ph.D. (ECE), IKGPTU, M.Tech (VLSI Design & CAD) Thapar University and B.Tech (Electronics and Instrumentation) from Kurukshetra University. She is GATE qualified with All India Rank 428. She has authored about 50 technical research papers in SCI, Scopus indexed quality journals, and national/international conferences. Dr. Rajkumar Sarma received his B.E. in Electronics and Communications Engineering from Vinayaka Mission’s University, Salem, India & M.Tech degree from Lovely Professional University, Phagwara, Punjab and currently pursuing Ph.D. from Lovely Professional University, Phagwara, Punjab.
A Cookbook that will help you implement Machine Learning algorithms and techniques by building real-world projects Key Features Learn how to handle an entire Machine Learning Pipeline supported with adequate mathematics. Create Predictive Models and choose the right model for various types of Datasets. Learn the art of tuning a model to improve accuracy as per Business requirements. Get familiar with concepts related to Data Analytics with Visualization, Data Science and Machine Learning. Description Machine Learning does not have to be intimidating at all. This book focuses on the concepts of Machine Learning and Data Analytics with mathematical explanations and programming examples. All the codes are written in Python as it is one of the most popular programming languages used for Data Science and Machine Learning. Here I have leveraged multiple libraries like NumPy, Pandas, scikit-learn, etc. to ease our task and not reinvent the wheel. There are five projects in total, each addressing a unique problem. With the recipes in this cookbook, one will learn how to solve Machine Learning problems for real-time data and perform Data Analysis and Analytics, Classification, and beyond. The datasets used are also unique and will help one to think, understand the problem and proceed towards the goal. The book is not saturated with Mathematics, but mostly all the Mathematical concepts are covered for the important topics. Every chapter typically starts with some theory and prerequisites, and then it gradually dives into the implementation of the same concept using Python, keeping a project in the background. What will you learn Understand the working of the O.S.E.M.N. framework in Data Science. Get familiar with the end-to-end implementation of Machine Learning Pipeline. Learn how to implement Machine Learning algorithms and concepts using Python. Learn how to build a Predictive Model for a Business case. Who this book is for This cookbook is meant for anybody who is passionate enough to get into the World of Machine Learning and has a preliminary understanding of the Basics of Linear Algebra, Calculus, Probability, and Statistics. This book also serves as a reference guidebook for intermediate Machine Learning practitioners. Table of Contents 1. Boston Crime 2. World Happiness Report 3. Iris Species 4. Credit Card Fraud Detection 5. Heart Disease UCI About the Author Rehan Guha —A Researcher by the day and an Artist by night. Our Author is a Scholar -lecturer, an Innovator, and also a Humanitarian -Philanthropist. He started his life as a Coder, Developer, and now he is into research in the field of Machine Learning and Algorithms but also has a keen interest in General Science, Technology, Invention & Innovation. The author holds a graduation degree from the Institute of Engineering & Management, Kolkata, and a Postgraduate certification on Deep Learning from the Indian Institute of Technology, Kharagpur (IIT-K)-AICTE approved FDP course. If we talk about Rehan's area of interest, it lies in Optimization Problems, Explainable AI, Deep Learning Architecture, Algorithms, Complexity, Algorithmic Thinking, et cetera… He has multiple publications through Journals and Open Publications, along with his publications he has filed multiple patents for his Innovations and Inventions. At an early age, one of his patents was also demonstrated to the Indian Army. In Rehan’s career, he has been involved with a variety of Business Verticals, starting from Banking, Consulting, Law, Insurance, Freight & Logistics, and Telcom.
Covers Data Science concepts, processes, and the real-world hands-on use cases. Key Features -Covers the journey from a basic programmer to an effective Data Science developer. -Applied use of Data Science native processes like CRISP-DM and Microsoft TDSP. -Implementation of MLOps using Microsoft Azure DevOps. Description "How is the Data Science project to be implemented?" has never been more conceptually sounding, thanks to the work presented in this book. This book provides an in-depth look at the current state of the world's data and how Data Science plays a pivotal role in everything we do. This book explains and implements the entire Data Science lifecycle using well-known data science processes like CRISP-DM and Microsoft TDSP. The book explains the significance of these processes in connection with the high failure rate of Data Science projects. The book helps build a solid foundation in Data Science concepts and related frameworks. It teaches how to implement real-world use cases using data from the HMDA dataset. It explains Azure ML Service architecture, its capabilities, and implementation to the DS team, who will then be prepared to implement MLOps. The book also explains how to use Azure DevOps to make the process repeatable while we're at it. By the end of this book, you will learn strong Python coding skills, gain a firm grasp of concepts such as feature engineering, create insightful visualizations and become acquainted with techniques for building machine learning models. What you will learn -Organize Data Science projects using CRISP-DM and Microsoft TDSP. -Learn to acquire and explore data using Python visualizations. -Get well versed with the implementation of data pre-processing and Feature Engineering. -Understand algorithm selection, model development, and model evaluation. -Hands-on with Azure ML Service, its architecture, and capabilities. -Learn to use Azure ML SDK and MLOps for implementing real-world use cases. Who this book is for This book is intended for programmers who wish to pursue AI/ML development and build a solid conceptual foundation and familiarity with related processes and frameworks. Additionally, this book is an excellent resource for Software Architects and Managers involved in the design and delivery of Data Science-based solutions. Table of Contents 1. Data Science for Business 2. Data Science Project Methodologies and Team Processes 3. Business Understanding and Its Data Landscape 4. Acquire, Explore, and Analyze Data 5. Pre-processing and Preparing Data 6. Developing a Machine Learning Model 7. Lap Around Azure ML Service 8. Deploying and Managing Models
Understanding and implementing the database management systems concepts in SQL and PL/SQL Key Features Practice SQL concepts by writing queries and perform your own data visualization and analysis. Gain insights on Entity Relationship Model and how to implement in your business environment. Series of question banks and case-studies to develop strong hold on RDBMS concepts. Description Relational Database Management Systems In-Depth brings the fundamental concepts of database management systems to you in more elaborated learning with conceptual clarity of RDBMS. This book brings an extensive coverage of theoretical concepts on types of databases, concepts of relational database management systems, normalization and many more. You will explore exemplification of Entity Relational Model concepts that would teach the readers to design accurate business systems. Backed with a series of examples, you can practice the fundamental concepts of RDBMS and SQL queries including Oracle’s SQL queries, MySQL and SQL Server. In addition to the illustration of concepts on SQL, there is an implementation of crucial business rules using PL/SQL based stored procedures and database triggers.Finally, by the end of this book there is a mention of the useful data oriented technologies like Big Data, Data Lake etc and the crucial role played by such techniques in the current data driven decisions. Throughout the book, you will come across key learnings and key terms that will help you to understand and revise the concepts learned. Along with this, you will also come across questions and case studies by the end of every chapter to prepare for job interviews and certifications. What you will learn Depiction of Entity Relationship Model with various business case studies. Illustration of the normalization concept to make the database stronger and consistent. Designing the successful client-server applications using PL/SQL concepts. Learning the concepts of OODBS and Database Design with Normalization and Relationships. Who this book is for This book is meant for academicians, students, developers and administrators including beginners and readers experienced in some other programming languages and database systems. Table of Contents 1. Database Systems Architecture 2. Database Management System Models 3. Relational query languages 4. Relational Database Design 5. Query Processing and Optimization 6. Transaction Processing 7. Implementation Techniques 8. SQL Concepts 9. PL/SQL Concepts 10. Collections in PL/SQL 11. What Next? About the Author Dr. Madhavi Vaidya is an experienced and qualified Assistant Professor with a demonstrated history of working in the education management industry . Skilled in programming languages like C, Python, SQL, Oracle Database, Dr. Madhavi has understanding and knowledge of Data Analytics, Information Retrieval, Software Engineering and Project Management. She has strong education professional with a Master of Computer Applications and Doctor of Philosophy in the subject of Computer Science and Engineering. One of the key areas of her research is Big Data analytics using Hadoop-MapReduce and various Big Data technologies. She is a Content Writer @Udemy and various other online courses are in her credit including BPB publications. Ample research papers are in her credit, presented and published in various National and International conference along with research chapters and articles in ACM, IEEE, Elsevier and Developer IQ magazine. Reviewing articles and research papers- Acting as a reviewer for the journals like IEEE Access, ASSA, IGI Global and many other prestigious journals. LinkedIn Profile: https://www.linkedin.com/in/dr-madhavi-v-01882327
Complete reference guide to Redis Key Features Complete coverage of Redis Modules. Best practices, tips and tricks, and expert techniques to scale Redis. Troubleshooting solutions to perform real-time faster data processing for client applications. Description This book begins with teaching you to set up your own Redis environment, followed by Redis data structures, their architecture, and use cases. You get to learn the details about Redis Modules such as RediSearch, RedisJSON, RedisTimeSeries, RedisAI, and RedisGraph with specific business use-case examples. This book makes you a Redis Expert by getting you hands-on with best practices on Redis and some tricks to scale Redis activities. What you will learn Redis’s advantages over the other NOSQL databases. Explore Redis Enterprise and its real gameplay in enterprise applications. Learn Redis data structures through practically demonstrated use cases. Learn from Industry expert to setup the Redis in production environment. Understand how Redis enterprise enhances Redis OSS. Who this book is for This book is ideal for anyone who is interested in understanding the basic concepts of the Redis database. The book will help the IT professionals, Software developers, Technical leads, Architects. Readers should have a working knowledge of database designing, basic programming skills, and an understanding of the latest trends in cloud computing. Table of Contents 1. Introduction to NoSQL World 2. NoSQL database types 3. Are NoSQL databases better than traditional databases? 4. History of Redis 5. Getting started with Redis 6. Setting up Redis 7. Redis Data Structures in details 8. Scaling Redis 9. Modules 10. Redis use cases 11. Redis as database service - enterprise solutions 12. What is new in Redis 6? 13. Appendix A  , , , , , ,(i) Using Redis-cli  , , , , , ,(ii) RedisInsight tool  , , , , , ,(iii) Community helps About the Author Suyog is a solutions architect at Redis Labs (a database unicorn company in Silicon Valley). Suyog is a technology evangelist, community helper, and has broad technical knowledge and business experience with a specialization in distributed, micro-services, low-latency, and high-throughput demand mission critical apps. He is a trusted advisor to Redis Labs customers, which include leading global banking institutions, fintechs, telcos, media, and financial service providers. LinkedIn Profile: Suyog Kale: https://www.linkedin.com/in/suyogkale// Chinmay is the founder and director of Hybrowlabs Technologies, a digital solutions and cloud consultancy company based out of Pune. He helps fortune 500 clients create awesome websites. He is a passionate speaker of OSS. In his free time, Chinmay likes to read non-fiction books on psychology, history, and philosophy. LinkedIn Profile: https://www.linkedin.com/in/cykulkarni/