Download or read book Learn Autonomous Programming with Python written by Varun P Divadkar and published by BPB Publications. This book was released on 2024-01-30 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash the hidden potential of Python to emerge as a change maker of contemporary industry KEY FEATURES ● Explore Python commands for RPA, workflows and hyperautomation. ● Concise chapters with lucid examples and elaborate codes that make learning interesting. ● Practical industry use case at the end of every chapter to highlight its real world application. DESCRIPTION The current industry (also called Industry 4.0) has witnessed an unprecedented expansion of technology in a short span of time, owing to an exponential increase in computational power coupled with internet technology. Consequently, domains like artificial intelligence, machine learning, deep learning and robotic process automation have gained prominence and become the backbone of organizations, making it inevitable for professionals to upgrade their skills in these domains. Orchestrate your work with AI and ML. Learn RPA's power, conduct web symphonies, utilize spreadsheets, and automate emails. You can also extract data from PDFs and images, choreograph applications, and play with deep learning. Design workflows, create hyperautomation finales, and combine Python with UiPath. You can further build a solid stage for your projects with PyScript, and continue with test automation. This book equips you to revolutionize your work, one Python script at a time. This book can be used as ready to reference as well as a user manual for quick solutions to common organizational needs and even for brushing up on key technical domain concepts. WHAT YOU WILL LEARN ● You will have a clear understanding of Python and create concise, flexible and maintainable applications for current industry needs. ● You will explore web scraping techniques using powerful libraries to extract valuable data from the web. ● You will have a high level overview of fundamentals in ML, deep learning, RPA, and hyperautomation. ● You will learn to write compact and maintainable code in Python catering to typical applications in contemporary industries. ● You will also learn how to apply your learnings to real world industry scenarios using the practical Python use cases presented at the end of each chapter. WHO THIS BOOK IS FOR This book is specifically meant for students and professionals who have prior working knowledge of Python from a basic to intermediate level and would want to expand their horizon of Python programming. TABLE OF CONTENTS 1. Why Python for Automation? 2. RPA Foundations 3. Getting Started with AI/ML in Python 4. Automating Web Scraping 5. Automating Excel and Spreadsheets 6. Automating Emails and Messaging 7. Working with PDFs and Images 8. Mechanizing Applications, Folders and Actions 9. Intelligent Automation Part 1: Using Machine Learning 10. Intelligent Automation Part 2: Using Deep Learning 11. Automating Business Process Workflows 12. Hyperautomation 13. Python and UiPath 14. Architecting Automation Projects 15. The PyScript Framework 16. Test Automation in Python

Download or read book Learning Robotics Using Python written by Lentin Joseph and published by Packt Publishing Ltd. This book was released on 2015-05-27 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are an engineer, a researcher, or a hobbyist, and you are interested in robotics and want to build your own robot, this book is for you. Readers are assumed to be new to robotics but should have experience with Python.

Download or read book Learn Robotics Programming written by Danny Staple and published by Packt Publishing Ltd. This book was released on 2018-11-29 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain experience of building a next-generation collaboration robot Key FeaturesGet up and running with the fundamentals of robotic programmingProgram a robot using Python and the Raspberry Pi 3Learn to build a smart robot with interactive and AI-enabled behaviorsBook Description We live in an age where the most difficult human tasks are now automated. Smart and intelligent robots, which will perform different tasks precisely and efficiently, are the requirement of the hour. A combination of Raspberry Pi and Python works perfectly when making these kinds of robots. Learn Robotics Programming starts by introducing you to the basic structure of a robot, along with how to plan, build, and program it. As you make your way through the book, you will gradually progress to adding different outputs and sensors, learning new building skills, and writing code for interesting behaviors with sensors. You’ll also be able to update your robot, and set up web, phone, and Wi-Fi connectivity in order to control it. By the end of the book, you will have built a clever robot that can perform basic artificial intelligence (AI) operations. What you will learnConfigure a Raspberry Pi for use in a robotInterface motors and sensors with a Raspberry PiImplement code to make interesting and intelligent robot behaviorsUnderstand the first steps in AI behavior such as speech recognition visual processingControl AI robots using Wi-FiPlan the budget for requirements of robots while choosing partsWho this book is for Learn Robotics Programming is for programmers, developers, and enthusiasts interested in robotics and developing a fully functional robot. No major experience required just some programming knowledge would be sufficient.

Download or read book Learn Robotics Programming written by Danny Staple and published by Packt Publishing Ltd. This book was released on 2021-02-12 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop an extendable smart robot capable of performing a complex series of actions with Python and Raspberry Pi Key Features Get up to speed with the fundamentals of robotic programming and build intelligent robots Learn how to program a voice agent to control and interact with your robot's behavior Enable your robot to see its environment and avoid barriers using sensors Book Description We live in an age where the most complex or repetitive tasks are automated. Smart robots have the potential to revolutionize how we perform all kinds of tasks with high accuracy and efficiency. With this second edition of Learn Robotics Programming, you'll see how a combination of the Raspberry Pi and Python can be a great starting point for robot programming. The book starts by introducing you to the basic structure of a robot and shows you how to design, build, and program it. As you make your way through the book, you'll add different outputs and sensors, learn robot building skills, and write code to add autonomous behavior using sensors and a camera. You'll also be able to upgrade your robot with Wi-Fi connectivity to control it using a smartphone. Finally, you'll understand how you can apply the skills that you've learned to visualize, lay out, build, and code your future robot building projects. By the end of this book, you'll have built an interesting robot that can perform basic artificial intelligence operations and be well versed in programming robots and creating complex robotics projects using what you've learned. What you will learn Leverage the features of the Raspberry Pi OS Discover how to configure a Raspberry Pi to build an AI-enabled robot Interface motors and sensors with a Raspberry Pi Code your robot to develop engaging and intelligent robot behavior Explore AI behavior such as speech recognition and visual processing Find out how you can control AI robots with a mobile phone over Wi-Fi Understand how to choose the right parts and assemble your robot Who this book is for This second edition of Learn Robotics Programming is for programmers, developers, and robotics enthusiasts who want to develop a fully functional robot and leverage AI to build interactive robots. Basic knowledge of the Python programming language will help you understand the concepts covered in this robot programming book more effectively.

Download or read book Learning Robotics using Python written by Lentin Joseph and published by Packt Publishing Ltd. This book was released on 2018-06-27 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, simulate, and program interactive robots Key Features Design, simulate, build, and program an interactive autonomous mobile robot Leverage the power of ROS, Gazebo, and Python to enhance your robotic skills A hands-on guide to creating an autonomous mobile robot with the help of ROS and Python Book Description Robot Operating System (ROS) is one of the most popular robotics software frameworks in research and industry. It has various features for implementing different capabilities in a robot without implementing them from scratch. This book starts by showing you the fundamentals of ROS so you understand the basics of differential robots. Then, you'll learn about robot modeling and how to design and simulate it using ROS. Moving on, we'll design robot hardware and interfacing actuators. Then, you'll learn to configure and program depth sensors and LIDARs using ROS. Finally, you'll create a GUI for your robot using the Qt framework. By the end of this tutorial, you'll have a clear idea of how to integrate and assemble everything into a robot and how to bundle the software package. What you will learn Design a differential robot from scratch Model a differential robot using ROS and URDF Simulate a differential robot using ROS and Gazebo Design robot hardware electronics Interface robot actuators with embedded boards Explore the interfacing of different 3D depth cameras in ROS Implement autonomous navigation in ChefBot Create a GUI for robot control Who this book is for This book is for those who are conducting research in mobile robotics and autonomous navigation. As well as the robotics research domain, this book is also for the robot hobbyist community. You’re expected to have a basic understanding of Linux commands and Python.

Download or read book Network Programmability and Automation written by Jason Edelman and published by "O'Reilly Media, Inc.". This book was released on 2018-02-02 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Like sysadmins before them, network engineers are finding that they cannot do their work manually anymore. As the field faces new protocols, technologies, delivery models, and a pressing need for businesses to be more agile and flexible, network automation is becoming essential. This practical guide shows network engineers how to use a range of technologies and tools—including Linux, Python, JSON, and XML—to automate their systems through code. Network programming and automation will help you simplify tasks involved in configuring, managing, and operating network equipment, topologies, services, and connectivity. Through the course of the book, you’ll learn the basic skills and tools you need to make this critical transition. This book covers: Python programming basics: data types, conditionals, loops, functions, classes, and modules Linux fundamentals to provide the foundation you need on your network automation journey Data formats and models: JSON, XML, YAML, and YANG for networking Jinja templating and its applicability for creating network device configurations The role of application programming interfaces (APIs) in network automation Source control with Git to manage code changes during the automation process How Ansible, Salt, and StackStorm open source automation tools can be used to automate network devices Key tools and technologies required for a Continuous Integration (CI) pipeline in network operations

Download or read book LEARN ROBOTICS PROGRAMMING written by DANNY. STAPLE and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Learning Robotics Using Python written by Joseph Lentin and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence with Python written by Prateek Joshi and published by Packt Publishing Ltd. This book was released on 2017-01-27 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.

Download or read book Mastering Reinforcement Learning with Python written by Enes Bilgin and published by Packt Publishing Ltd. This book was released on 2020-12-18 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices Key FeaturesUnderstand how large-scale state-of-the-art RL algorithms and approaches workApply RL to solve complex problems in marketing, robotics, supply chain, finance, cybersecurity, and moreExplore tips and best practices from experts that will enable you to overcome real-world RL challengesBook Description Reinforcement learning (RL) is a field of artificial intelligence (AI) used for creating self-learning autonomous agents. Building on a strong theoretical foundation, this book takes a practical approach and uses examples inspired by real-world industry problems to teach you about state-of-the-art RL. Starting with bandit problems, Markov decision processes, and dynamic programming, the book provides an in-depth review of the classical RL techniques, such as Monte Carlo methods and temporal-difference learning. After that, you will learn about deep Q-learning, policy gradient algorithms, actor-critic methods, model-based methods, and multi-agent reinforcement learning. Then, you'll be introduced to some of the key approaches behind the most successful RL implementations, such as domain randomization and curiosity-driven learning. As you advance, you’ll explore many novel algorithms with advanced implementations using modern Python libraries such as TensorFlow and Ray’s RLlib package. You’ll also find out how to implement RL in areas such as robotics, supply chain management, marketing, finance, smart cities, and cybersecurity while assessing the trade-offs between different approaches and avoiding common pitfalls. By the end of this book, you’ll have mastered how to train and deploy your own RL agents for solving RL problems. What you will learnModel and solve complex sequential decision-making problems using RLDevelop a solid understanding of how state-of-the-art RL methods workUse Python and TensorFlow to code RL algorithms from scratchParallelize and scale up your RL implementations using Ray's RLlib packageGet in-depth knowledge of a wide variety of RL topicsUnderstand the trade-offs between different RL approachesDiscover and address the challenges of implementing RL in the real worldWho this book is for This book is for expert machine learning practitioners and researchers looking to focus on hands-on reinforcement learning with Python by implementing advanced deep reinforcement learning concepts in real-world projects. Reinforcement learning experts who want to advance their knowledge to tackle large-scale and complex sequential decision-making problems will also find this book useful. Working knowledge of Python programming and deep learning along with prior experience in reinforcement learning is required.

Download or read book Learn Raspberry Pi Programming with Python written by Wolfram Donat and published by Apress. This book was released on 2014-05-08 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Raspberry Pi Programming with Python will show you how to program your nifty new $35 computer to make a web spider, a weather station, a media server, and more. You'll learn how to program in Python on your Raspberry Pi with hands-on examples and fun projects. Even if you're completely new to programming in general, you'll figure out how to create a home security system, an underwater photography system, an RC plane with a camera, and even a near-space weather balloon with a camera. You'll learn how to make a variety of fun and even useful projects, from a web bot to search and download files to a toy to drive your pets insane. You'll even learn how to use Pi with Arduino as well as Pi with Gertboard, an expansion board with an onboard ATmega microcontroller.

Download or read book Applied Deep Learning and Computer Vision for Self Driving Cars written by Sumit Ranjan and published by Packt Publishing Ltd. This book was released on 2020-08-14 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore self-driving car technology using deep learning and artificial intelligence techniques and libraries such as TensorFlow, Keras, and OpenCV Key FeaturesBuild and train powerful neural network models to build an autonomous carImplement computer vision, deep learning, and AI techniques to create automotive algorithmsOvercome the challenges faced while automating different aspects of driving using modern Python libraries and architecturesBook Description Thanks to a number of recent breakthroughs, self-driving car technology is now an emerging subject in the field of artificial intelligence and has shifted data scientists' focus to building autonomous cars that will transform the automotive industry. This book is a comprehensive guide to use deep learning and computer vision techniques to develop autonomous cars. Starting with the basics of self-driving cars (SDCs), this book will take you through the deep neural network techniques required to get up and running with building your autonomous vehicle. Once you are comfortable with the basics, you'll delve into advanced computer vision techniques and learn how to use deep learning methods to perform a variety of computer vision tasks such as finding lane lines, improving image classification, and so on. You will explore the basic structure and working of a semantic segmentation model and get to grips with detecting cars using semantic segmentation. The book also covers advanced applications such as behavior-cloning and vehicle detection using OpenCV, transfer learning, and deep learning methodologies to train SDCs to mimic human driving. By the end of this book, you'll have learned how to implement a variety of neural networks to develop your own autonomous vehicle using modern Python libraries. What you will learnImplement deep neural network from scratch using the Keras libraryUnderstand the importance of deep learning in self-driving carsGet to grips with feature extraction techniques in image processing using the OpenCV libraryDesign a software pipeline that detects lane lines in videosImplement a convolutional neural network (CNN) image classifier for traffic signal signsTrain and test neural networks for behavioral-cloning by driving a car in a virtual simulatorDiscover various state-of-the-art semantic segmentation and object detection architecturesWho this book is for If you are a deep learning engineer, AI researcher, or anyone looking to implement deep learning and computer vision techniques to build self-driving blueprint solutions, this book is for you. Anyone who wants to learn how various automotive-related algorithms are built, will also find this book useful. Python programming experience, along with a basic understanding of deep learning, is necessary to get the most of this book.

Download or read book Learn Python written by Damon Parker and published by Damon Parker. This book was released on 2021-06-12 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python programming language has rendered itself as the language of choice for coding beginners and advanced software programmers alike. This book is written to help you master the basic concepts of Python coding and how you can utilize your coding skills to analyze a large volume of data and uncover valuable information that can otherwise be easily lost in the volume. It was designed primarily to emphasize the readability of the programming code, and its syntax enables programmers to convey ideas using fewer lines of code. Python programming language increases the speed of operation while allowing for higher efficiency in creating system integrations. Some of the highlights of the book include: - Key features and advantages of learning to code Python as well as the history of how Python programming was created - Step-by-step instructions on how to install Python on your operating systems (Windows, Mac, and Linux) - The concept of Python data types is presented in exquisite detail with various examples of each data type - How to create Python variables - Comprehensive lists of a variety of built-in functions and methods supported by Python - Basic concepts of writing efficient and effective Python codes, focusing on various programming elements - How to write if and else statements to retrieve desired information from your data - For and While loops are explained with explicit details in an easy-to-understand language - Basic concepts of big data analysis and machine learning algorithms - A brief overview of various renowned machine learning libraries All the concepts are explained with standard Python coding syntax supported with relevant examples and followed by exercises to help you test and verify your understanding of those concepts. Finally, as an added bonus you will learn some Python tips and tricks to take your machine learning programming game to the next level. Remember, knowledge is power, and with the great power you will gather from this book, you will be armed to make sound personal and professional technological choices. Your Python programming skillset will improve drastically, and you will be poised to develop your very own machine learning model! Don't you think it can be that easy? If you really want to have proof of all this, don't waste any more time! Grab your copy now!

Download or read book Python for Beginners written by Learning Python In Deep and published by Bookly Limited. This book was released on 2021-01-15 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: If You Are Looking For A Guide That Introduces You Step By Step Into The Articulated World Of Python Programming Then Keep Reading It can be difficult to get started with coding if you have not the right support. You may have looked at some of the most popular coding languages, such as C++ or Java and were a little scared of what you have seen. You may have bought ebooks that have been filled to the edge with letters and symbols that you just didn't understand, and you were frustrated and just wanted to go away. Many people are afraid of programming and feel like it's just too hard. But with this Python programming language guide, filled with examples and exercises, you will find that even some of the more complex parts of the code are going to be easier to handle and you will find that it can be easier than ever to learn about coding and even to read it as a professional. This guide will give the basic principles you need to start with Python programming. We will start a little talk about what Python programming is, as well as some of the steps you need to take to download the program and gives you some more information to actually understand why this program is so GREAT. We will then step further to some keywords that will be useful to you when you start the program and even talk about the pros and cons of using Python for all your coding and app needs. The rest of the guide is dedicated to talking about some of the different things you can do with the Python Program as well as various examples of how each of them work. We are talking about adding comments in the code, working with strings and integers, and even working with variables so that they will display correctly in the program. Here Are Some Of The Information You Will Find: Why You Should Select Python As Your Language? Which Version Of Python Should You Have? Installing The Python Language In Three Of The Most Common Operating Systems All You Need To Know About Python Variables And Python Numbers How To Create, Replicate and Store Python Strings (and other 13 activities about strings) Acquire The Necessary Knowledge To Get Hired In Many Companies The Six Most Important Things To Know About Operators And Expressions And More And More About Python Tuples And Sets, Conditional Execution And Iteration Even if you've never written or seen a programming code in your whole life; Even if you've never used a coding programm; Even if you are bad or have no experience at coding, do not need to worry because this guide was written to guide complete beginners like you. Don't Waste Any More Time To Achieve Your Goals Scrolling Up And Ordering Now!

Download or read book Learning Robotics Using Python written by Lentin Joseph and published by . This book was released on 2018-06-27 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, simulate, and program interactive robots Key Features Design, simulate, build, and program an interactive autonomous mobile robot Leverage the power of ROS, Gazebo, and Python to enhance your robotic skills A hands-on guide to creating an autonomous mobile robot with the help of ROS and Python Book Description Robot Operating System (ROS) is one of the most popular robotics software frameworks in research and industry. It has various features for implementing different capabilities in a robot without implementing them from scratch. This book starts by showing you the fundamentals of ROS so you understand the basics of differential robots. Then, you'll learn about robot modeling and how to design and simulate it using ROS. Moving on, we'll design robot hardware and interfacing actuators. Then, you'll learn to configure and program depth sensors and LIDARs using ROS. Finally, you'll create a GUI for your robot using the Qt framework. By the end of this tutorial, you'll have a clear idea of how to integrate and assemble everything into a robot and how to bundle the software package. What you will learn Design a differential robot from scratch Model a differential robot using ROS and URDF Simulate a differential robot using ROS and Gazebo Design robot hardware electronics Interface robot actuators with embedded boards Explore the interfacing of different 3D depth cameras in ROS Implement autonomous navigation in ChefBot Create a GUI for robot control Who this book is for This book is for those who are conducting research in mobile robotics and autonomous navigation. As well as the robotics research domain, this book is also for the robot hobbyist community. You're expected to have a basic understanding of Linux commands and Python.

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Download or read book Hands On Vision and Behavior for Self Driving Cars written by Luca Venturi and published by Packt Publishing Ltd. This book was released on 2020-10-23 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to learning visual perception for self-driving cars for computer vision and autonomous system engineers Key FeaturesExplore the building blocks of the visual perception system in self-driving carsIdentify objects and lanes to define the boundary of driving surfaces using open-source tools like OpenCV and PythonImprove the object detection and classification capabilities of systems with the help of neural networksBook Description The visual perception capabilities of a self-driving car are powered by computer vision. The work relating to self-driving cars can be broadly classified into three components - robotics, computer vision, and machine learning. This book provides existing computer vision engineers and developers with the unique opportunity to be associated with this booming field. You will learn about computer vision, deep learning, and depth perception applied to driverless cars. The book provides a structured and thorough introduction, as making a real self-driving car is a huge cross-functional effort. As you progress, you will cover relevant cases with working code, before going on to understand how to use OpenCV, TensorFlow and Keras to analyze video streaming from car cameras. Later, you will learn how to interpret and make the most of lidars (light detection and ranging) to identify obstacles and localize your position. You’ll even be able to tackle core challenges in self-driving cars such as finding lanes, detecting pedestrian and crossing lights, performing semantic segmentation, and writing a PID controller. By the end of this book, you’ll be equipped with the skills you need to write code for a self-driving car running in a driverless car simulator, and be able to tackle various challenges faced by autonomous car engineers. What you will learnUnderstand how to perform camera calibrationBecome well-versed with how lane detection works in self-driving cars using OpenCVExplore behavioral cloning by self-driving in a video-game simulatorGet to grips with using lidarsDiscover how to configure the controls for autonomous vehiclesUse object detection and semantic segmentation to locate lanes, cars, and pedestriansWrite a PID controller to control a self-driving car running in a simulatorWho this book is for This book is for software engineers who are interested in learning about technologies that drive the autonomous car revolution. Although basic knowledge of computer vision and Python programming is required, prior knowledge of advanced deep learning and how to use sensors (lidar) is not needed.