COM051360 books

Come and join hands together to learn Python from scratch. This book will help you understand Python from scratch and help you build a career in the field of programming. Key Features -Exciting examples and a solid grasp of the principles of Python. -An easy guide for absolute beginners to enjoy coding while learning. -Exception handling, OOPs fundamentals, inheritance, and reusability explained in detail. Description The book offers to teach a novice programmer the fundamentals of Python programming from the ground up. The book provides a brief history of Python, followed by exploring Python's fundamental concepts, features, and applications in detail. The book explains Python identifiers, keywords, variables, and assignments, as well as basic operators and decision-making statements. This book covers repetitive code, strings and integers (dictionaries), functions and modules (files), exception handling, and object-oriented programming in all of its variants. The book explains concepts with illustrations, thus making it simple for even the most unskilled reader to grasp the basics of the code execution flow. By the end of this book, you will have a firm grasp of all of Python's programming ideas. Additionally, it will help you to prepare for any upcoming job interviews with your comprehensive Python understanding. What you will learn -Quickly grasp the concepts of lists, tuples, dictionaries, and functions. -Examine Python's effective use of exception handling. -Makes object-oriented programming more understandable. -Discover when and how to use Python's decision-making statements. -Use Python to perform and execute file operations. Who this book is for This book is for web application developers, entry level developers, and IT graduates who want to learn the entire web application development by developing a solid hold on Python principles. Basic programming knowledge is recommended but not required. Table of Contents 1. Introduction 2. Basic Syntax 3. Variable Types 4. Basic Operators 5. Decision Making 6. Repeating Code Using Loops 7. Numbers 8. Strings 9. Lists 10. Tuples 11. Dictionaries 12. Functions 13. Modules 14. Files I/O 15. Exception Handling 16. Object-Oriented Programming

Learn the most popular software programming language in easy steps Key Features -Extensive coverage on fundamentals and core concepts of Python programming. -A complete reference guide to crack Python Interviews and exams. -Includes ample MCQs and solved examples to prepare you for theory and practical exams. -Easy-to-understand text with explanatory illustrations. Description Basic Core Python Programming is an absolute beginners book. It focuses on the fundamentals of Python programming and simplifies coding concepts. This book makes it easy to learn the concepts of Python variables, Expressions, Decision structures, and Iteration. Equipped with a lot of exercises and Q&As, you don’t just practice the programming but also gain an in-depth understanding of the basic concepts of Python. You will start your journey right from how to go about Python installation and start using its interactive development environment and go on to learn how to build logic and implement it with coding. You will explore different types of data, operators, and in-built functions. This book covers numerous coding examples that will help you understand the importance of each data type, how to work with each one of them, and when to use them. You can learn some more practical useful concepts like how to implement control structures and use them for decision making and controlling the program flow. What you will learn -Stronghold on Python variables, expressions, decision structures, and iterations. -Practical knowledge on how to work with various data types, operators, and in-built functions. -Learn to implement strings, lists, arrays, and control structures. -Learn how to control the program flow and how to use it for decision-making. -A great reference book on Python basics for software programmers. Who this book is for This book is highly appealing to all tech-savvy students, programming enthusiasts, IT undergraduates, and computer science students. You do not need any prior knowledge of programming to begin with this book as long as you have the interest to learn to program. Table of Contents 1. Introduction 2. Python Basics 3. Numbers, Operators, and In-built Functions 4. Strings 5. Lists and Arrays 6. Tuples and Dictionaries 7. Sets and Frozen Sets 8. Program Flow Control in Python About the Authors Mrs Meenu Kohli, author of ‘Python Interview Questions - Ultimate Guide to Success’ has authored another book ‘Python Programming for Graduates’. She has written this book for college students with the aim of making the concepts of Python programming easier for them. She holds a degree in BE (Electronics) from D.Y. Patil College of Engineering, Pune University. She has worked as a developer, tester, and trainer with some reputed MNCs and has a lot of experience in software development and testing. She has worked on projects related to Python, Java, EJB, C, C++, PHP, JSP, JavaScript, HTML, .NET, R, MySQL, Oracle, DB2, and Software Testing LinkedIn profile: https://www.linkedin.com/in/meenukohli78/

A practical guide for the rapid web application development with Flask Key Features Expert-led coverage of core capabilities of Flask, key extensions and its implementation. Explore the Werkzeug toolkit and Jinja Template engine and see how Flask interacts with JavaScript and CSS. Detailed modules on building and deploying RESTful applications using Flask. Description This book teaches the reader the complete workflow of developing web applications using Python and its most outperforming microframework, Flask. The book begins with getting you up to speed in developing a strong understanding of the web application development process and how Python is used in developing the applications. You will learn how to write your own first Flask-based web application in Python. You will learn about web gateway interfaces, including CGI and WSGI along with various tools like the Jinja 2 engine, Werkzeug toolkit, and Click toolkit. You will learn and practice the core features of Flask such as URL routing, rendering, handling static assets of a web application, how to handle cookies and sessions, and other HTTP objects. Once you have developed a strong knowledge of Flask, you will now dive deeper into advanced topics that includes Flask extensions for working with relational and NOSQL databases, Flask_WTF, and Flask-Bootstrap. You will explore design patterns, various blueprints on how to build modular and scalable applications, and finally how to deploy the RESTful APIs successfully on your own. What you will learn Get to know everything about the core capabilities of Flask. Understand the basic building blocks of Flask. Get familiar with advanced features of Flask, including blueprints, Flask extensions, and database connectivity. Get ready to design your own Flask-based web applications and RESTful APIs. Learn to build modular and scalable applications and how to deploy them successfully. Who this book is for This book is ideal for Python enthusiasts, open source contributors, and web app developers who intend to add Python web technologies in their skillsets and startup companies. The understanding of the core Python language with intermediate level expertise is required and experience of working with SQL, HTML, CSS, and JavaScript is an added advantage. Table of Contents 1. Python for CGI 2. WSGI 3. Flask Fundamentals 4. URL Routing 5. Rendering Templates 6. Static Files 7. HTTP Objects 8. Using Databases 9. More Flask Extensions 10. Blueprints and Contexts 11. Web API with Flask 12. Deploying Flask Applications 13. Appendix About the Author Malhar Lathkar is an independent software professional, corporate trainer, freelance technical writer, and Subject Matter Expert with an experience of more than three decades. He has trained hundreds of students/professionals in Python, Data Science, Java and Android, PHP and web development, etc. He also has the experience of delivering talks and conducting workshops on various IT topics.He writes regularly in a local newspaper on sports and technology-related current topics. LinkedIn Profile: https://www.linkedin.com/in/malharlathkar

Know Data science with numpy, pandas, scipy, sklearn Key Features Questions related to core/basic Python, Excel, basic and advanced statistics are included Book will prove to be a companion whenever you want to go for an interview Simple to use words have been used in the answers for the questions to help ease of remembering Description “Data science and Machine learning interview questions using Python,” a book which is a true companion of people aspiring for data science and machine learning, and it provides answers to most asked questions in an easy to remember and presentable form. Book mainly intended to be used as last-minute revision, before the interview, as all the important concepts and various terminologies have been given in a very simple and understandable format. Many examples have been provided so that the same can be used while giving answers in an interview. The book is divided into six chapters, which starts with the Data Science Basic Questions and Terms then covers the questions related to Python Programming, Numpy, Pandas, Scipy, and its Applications, then at the last covers Matplotlib and Statistics with Excel Sheet. What will you learn You can learn the basic concept and terms related to Data Science, python programming You will get to learn how to program in python, basics of Numpy You will get familiarity with the questions asked in an interview related to Pandas and learn the concepts of Scipy, Matplotib, and Statistics with Excel Sheet Who this book is for The book is mainly intended to help people represent their answer in a sensible way to the interviewer. The answers have been carefully rendered in a way to make things quite simple and yet represent the seriousness and complexity of the matter. Since data science is incomplete without mathematics, we have also included a part of the book dedicated to statistics. Table of Contents 1. Data Science Basic Questions and Terms 2. Python Programming Questions 3. Numpy Interview Questions 4. Pandas Interview Questions 5. Scipy and its Applications 6. Matplotlib Samples to Remember 7. Statistics with Excel Sheet About the Author Vishwanathan has twenty years of hard code experience in the software industry spanning across many multinational companies and domains. Playing with data to derive meaningful insights has been his domain, and that is what took him towards data science and machine learning.

Step-by-step guide to practising data science techniques with Jupyter notebooks Key Features Acquire Python skills to do independent data science projects Learn the basics of linear algebra and statistical science in Python way Understand how and when they're used in data science Build predictive models, tune their parameters and analyze performance in few steps Cluster, transform, visualize, and extract insights from unlabelled datasets Learn how to use matplotlib and seaborn for data visualization Implement and save machine learning models for real-world business scenarios Description Modern businesses are awash with data, making data driven decision-making tasks increasingly complex. As a result, relevant technical expertise and analytical skills are required to do such tasks. This book aims to equip you with just enough knowledge of Python in conjunction with skills to use powerful tool such as Jupyter Notebook in order to succeed in the role of a data scientist. The book starts with a brief introduction to the world of data science and the opportunities you may come across along with an overview of the key topics covered in the book. You will learn how to setup Anaconda installation which comes with Jupyter and preinstalled Python packages. Before diving in to several supervised, unsupervised and other machine learning techniques, you’ll learn how to use basic data structures, functions, libraries and packages required to import, clean, visualize and process data. Several machine learning techniques such as regression, classification, clustering, time-series etc have been explained with the use of practical examples and by comparing the performance of various models. By the end of the book, you will come across few case studies to put your knowledge to practice and solve real-life business problems such as building a movie recommendation engine, classifying spam messages, predicting the ability of a borrower to repay loan on time and time series forecasting of housing prices. Remember to practice additional examples provided in the code bundle of the book to master these techniques. Audience The book is intended for anyone looking for a career in data science, all aspiring data scientists who want to learn the most powerful programming language in Machine Learning or working professionals who want to switch their career in Data Science. While no prior knowledge of Data Science or related technologies is assumed, it will be helpful to have some programming experience. Table of Contents Data Science Fundamentals Installing Software and Setting up Lists and Dictionaries Function and Packages NumPy Foundation Pandas and Dataframe Interacting with Databases Thinking Statistically in Data Science How to import data in Python? Cleaning of imported data Data Visualization Data Pre-processing Supervised Machine Learning Unsupervised Machine Learning Handling Time-Series Data Time-Series Methods Case Study – 1 Case Study – 2 Case Study – 3 Case Study – 4 About the Author Prateek is a Data Enthusiast and loves the data driven technologies. Prateek has total 7 years of experience and currently he is working as a Data Scientist in an MNC. He has worked with finance and retail clients and has developed Machine Learning and Deep Learning solutions for their business. His keen area of interest is in natural language processing and in computer vision. In leisure he writes posts about Data Science with Python in his blog.

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

A step-by-step guide to implementing Continuous Integration and Continuous Delivery (CICD) for Mobile, Hybrid, and Web applications Key Features Understand how and when Continuous Integration makes a difference Learn how to create Declarative Pipeline for Continuous Integration and Continuous Delivery Understand the importance of Continuous Code Inspection and Code Quality Learn to publish Unit Test and Code Coverage in Declarative Pipeline Understand the importance of Quality Gates and Build Quality Description The main objective of the book is to create Declarative Pipeline for programming languages such as Java, Android, iOS, AngularJS, NodeJS, Flutter, Ionic Cordova, and .Net. The book starts by introducing all the areas which encompass the field of DevOps Practices. It covers definition of DevOps, DevOps history, benefits of DevOps culture, DevOps and Value Streams, DevOps practices, different Pipeline types such as Build Pipeline, Scripted Pipeline, Declarative Pipeline, and Blue Ocean. Each chapter focuses on Pipeline that includes Static Code Analysis using SonarQube or Lint tools, Unit tests, calculating code coverage, publishing unit tests and coverage reports, verifying the threshold of code coverage, creating build/package, and distributing package to a specific environment based on the type of programming language. The book will also teach you how to use different deployment distribution environments such as Azure App Services, Docker, Azure Container Services, Azure Kubernetes Service, and App Center. By the end, you will be able to implement DevOps Practices using Jenkins effectively and efficiently. What you will learn Use Multi-Stage Pipeline (Pipeline as a Code) to implement Continuous Integration and Continuous Delivery. Create and configure Cloud resources using Platform as a Service Model Deploy apps to Azure App Services, Azure Kubernetes and containers Understand how to distribute Mobile Apps (APK and IPA) to App Center Improve Code Quality and Standards using Continuous Code Inspection Who this book is for This book is for DevOps Consultants, DevOps Evangelists, DevOps Engineers, Technical Specialists, Technical Architects, Cloud Experts, and Beginners. Having a basics knowledge of Application development and deployment, Cloud Computing, and DevOps Practices would be an added advantage. Table of Contents 1. Introducing DevOps 2. Introducing Jenkins 2.0 and Blue Ocean 3. Building CICD Pipeline for Java Web Application 4. Building CICD Pipeline for Android App 5. Building CICD Pipeline for iOS App 6. Building CICD Pipeline for Angular Application 7. Building CICD Pipeline NodeJS Application 8. Building CICD Pipeline for Hybrid Mobile Application 9. Building CICD Pipeline for Python Application 10. Building CICD Pipeline for DotNet Application 11. Best Practices About the Author Mitesh is a DevOps engineer. He is in love with the DevOps culture and concept. Continuous improvement is his motto in life with existing imperfection. His primary focus is on the improvement of the existing culture of an organization or a project using Continuous Integration and Continuous Delivery. Ankita is a DevOps evangelist. She is a continuous learner and practitioner of Agile and DevOps. As a change agent, she always tries to bring change in an organization to get maximum benefits of DevOps. So, she wants to share her knowledge and make sure IT professionals are trained and empowered to make those changes.

A step-by-step guide that will help you manage data in a relational database using SQL with ease Key Features Understand the concepts related to relational databases. Learn how to install MariaDB and MySQL on Windows, Linux and tools to access it. Learn how to connect Python and Pandas to MySQL/MariaDB. Description This book starts with the concepts in RDBMS (Relational Database Management Systems) and SQL (Structured Query Language). The first few chapters cover the definitions and a brief explanation of all the important concepts. They also cover the installation of MariaDB and MySQL on Windows and Raspberry Pi, as well as the setup of various tools used to connect to MySQL and MariaDB server processes. We will also understand how to install sample schemas and how to use basic SQL queries. Then we move on to the SELECT query in detail. The book explores the data retrieval aspect of SQL queries in detail with the WHERE clause and NULL handling in detail. The book also explores the functions available in MySQL. Those are single row and group functions. Then we explore how to combine the data from multiple sources. The technique is known as Joins, and we will learn ANSI style and the old-style syntax for all the types of Joins. The last part explores the DDL and DMLs in depth. We also learn the concepts of Transactions and Constraints. The book explores how we can run the SQL queries from a Python 3 program and load a pandas DataFrame with the data from a table in a schema in the MySQL database. What will you learn Understand the basics of MySQL and MariaDB. Get familiar with MySQL Arithmetic Operators, DDL, DML, DCL & TCL commands. Understand the concept of Single-Row Functions and Group Functions in detail. Retrieve data from multiple sources using the Joins. Who this book is for This book is designed for beginners as well as professionals alike. The book will also be useful to Data Scientists, Data Analysts, Database Administrators, and Data Engineers. Table of Contents 1. Introduction and Installation 2. Getting Started with MySQL 3. Getting Started with SQL Queries 4. The WHERE clause in detail 5. Single Row Functions 6. Group Functions 7. Joins in MySQL 8. Subqueries 9. DDL, DML, and Transactions 10. Views 11. Python 3, MySQL, and Pandas About the Author Ashwin is an experienced veteran who, for the past 25 years, has been working with STEM (Science, Technology, Engineering, and Mathematics). In his career, Ashwin has worked for more than 7 years as an employee for various IT companies and Software Product Companies. He has written more than 2 dozen books on Arduino, Python programming, Computer Vision, IoT, databases, and other popular topics with BPB and other international publications. He has also reviewed many other technical books. He also creates courses for BPB and other platforms and teaches to 60000 students online. He has been working as a freelancer since 2017. He got his first taste in writing in 2015 when he wrote his first book on Raspberry Pi. In his free time, Ashwin makes videos for his Youtube channel, which has 10000 subscribers now. Outside work, Ashwin volunteers his spare time as a STEM Ambassador, helping, coaching, and mentoring young people in taking up careers in technology. Your Blog links: https://www.youtube.com/ashwinpajankar Your LinkedIn Profile: https://www.linkedin.com/in/ashwinpajankar/

Get familiar with various Supervised, Unsupervised and Reinforcement learning algorithms Key FeaturesUnderstand the types of Machine learning. Get familiar with different Feature extraction methods. Get an overview of how Neural Network Algorithms work.Learn how to implement Decision Trees and Random Forests. The book not only explains the Classification algorithms but also discusses the deviations/ mathematical modeling.Description This book covers important concepts and topics in Machine Learning. It begins with Data Cleansing and presents an overview of Feature Selection. It then talks about training and testing, cross-validation, and Feature Selection. The book covers algorithms and implementations of the most common Feature Selection Techniques. The book then focuses on Linear Regression and Gradient Descent. Some of the important Classification techniques such as K-nearest neighbors, logistic regression, Naïve Bayesian, and Linear Discriminant Analysis are covered in the book. It then gives an overview of Neural Networks and explains the biological background, the limitations of the perceptron, and the backpropagation model. The Support Vector Machines and Kernel methods are also included in the book. It then shows how to implement Decision Trees and Random Forests. Towards the end, the book gives a brief overview of Unsupervised Learning. Various Feature Extraction techniques, such as Fourier Transform, STFT, and Local Binary patterns, are covered. The book also discusses Principle Component Analysis and its implementation. What will you learnLearn how to prepare Data for Machine Learning.Learn how to implement learning algorithms from scratch.Use scikit-learn to implement algorithms.Use various Feature Selection and Feature Extraction methods.Learn how to develop a Face recognition system. Who this book is for The book is designed for Undergraduate and Postgraduate Computer Science students and for the professionals who intend to switch to the fascinating world of Machine Learning. This book requires basic know-how of programming fundamentals, Python, in particular.Table of Contents 1. An introduction to Machine Learning 2. The beginning: Pre-Processing and Feature Selection 3. Regression 4. Classification 5. Neural Networks- I 6. Neural Networks-II 7. Support Vector machines 8. Decision Trees 9. Clustering 10. Feature Extraction Appendix A1. Cheat Sheets A2. Face Detection A3.Biblography About the Author Harsh Bhasin is an Applied Machine Learning researcher. Mr. Bhasin worked as Assistant Professor in Jamia Hamdard, New Delhi, and taught as a guest faculty in various institutes including Delhi Technological University. Before that, he worked in C# Client-Side Development and Algorithm Development. Mr. Bhasin has authored a few papers published in renowned journals including Soft Computing, Springer, BMC Medical Informatics and Decision Making, AI and Society, etc. He is the reviewer of prominent journals and has been the editor of a few special issues. He has been a recipient of a distinguished fellowship. Outside work, he is deeply interested in Hindi Poetry, progressive era, Hindustani Classical Music, percussion instruments. His areas of interest include Data Structures, Algorithms Analysis and Design, Theory of Computation , Python, Machine Learning and Deep learning. Your LinkedIn Profile: https://in.linkedin.com/in/harsh-bhasin-69134426

Step-by-step guide to learn and solve complex computational problems with Nature Inspired algorithms. Key Features Artificial Neural Networks Deep Learning models using Keras Quantum Computers and Programming Genetic Algorithms, CNN and RNNs Swarm Intelligence Systems Reinforcement Learning using OpenAI Artificial Life DNA computing Fractals Description Natural Computing is the field of research inspired by nature, that allows the development of new algorithms to solve complex problems, leads to the synthesis of natural models, and may result in the design of new computing systems. This book exactly aims to educate you with practical examples on topics of importance associated with research field of Natural computing. The initial few chapters will quickly walk you through Neural Networks while describing deep learning architectures such as CNN, RNN and AutoEncoders using Keras. As you progress further, you’ll gain understanding to develop genetic algorithm to solve traveling saleman problem, implement swarm intelligence techniques using the SwarmPackagePy and Cellular Automata techniques such as Game of Life, Langton's ant, etc. The latter half of the book will introduce you to the world of Fractals such as such as the Cantor Set and the Mandelbrot Set, develop a quantum program with the QiSkit tool that runs on a real quantum computing platform, namely the IBM Q Machine and a Python simulation of the Adleman experiment that showed for the first time the possibility of performing computations at the molecular level. What You Will Learn Mastering Artificial Neural Networks Developing Artificial Intelligence systems Resolving complex problems with Genetic Programming and Swarm intelligence algorithms Programming Quantum Computers Exploring the mathematical world of fractals Simulating complex systems by Cellular Automata Understanding the basics of DNA computation Who This Book Is For This book is for all science enthusiasts, in particular who want to understand what are the links between computer sciences and natural systems. Interested readers should have good skills in math and python programming along with some basic knowledge of physics and biology. . Although, some knowledge of the topics covered in the book will be helpful, it is not essential to have worked with the tools covered in the book. Table of Contents Neural Networks Deep Learning Genetic Programming Swarm Intelligence Cellular Automata Fractals Quantum Computing DNA Computing About the Author Giancarlo Zaccone has over ten years of experience in managing research projects in scientific and industrial areas. He is a Software and Systems Engineer Consultant at European Space Agency (ESTEC). Giancarlo holds a master’s degree in Physics and an advanced master’s degree in Scientific Computing at La Sapienza of Rome. His LinkedIn Profile: https://www.linkedin.com/in/giancarlozaccone/