How to Build Self-Driving Cars From Scratch, Part 2 PDF Download
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Author: Bolakale Aremu
Publisher: AB Publisher LLC
ISBN:
Category : Computers
Languages : en
Pages : 93
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Book Description
This is part 2 of my 3-part training guide on how to build self-driving cars from scratch. This guide is bundled with a repository containing simulations, python scripts, graphics, and other useful assets. In this step-by-step guide, I teach you how to make an app that you can use to create a simulation where cars learn how to drive autonomously over racing tracks. Here’s a break down of the contents of this guide. Part 1: Car mechanics. In this part, you’ll learn how to draw the car and control it with the keyboard. You will use a multimedia library for Python called Pyglet. (https://pyglet.org/). This is the only library you will use in this guide. This is a cross-platform windowing and multimedia library for Python. It’s a powerful yet easy-to-use Python library for building games and other visually rich applications on Windows, macOS, and Linux. Part 2:Neural network and genetic algorithm. You’ll learn how to create the AI where you combine a neural network and genetic algorithm. You’ll learn how to add sensors to the car and get output from them. To prevent the untrained network from car crashes, a genetic algorithm will be used to train the cars. This will help the cars to drive simple tracks. Part 3: Challenges. You’ll add some challenges to the system. Tracks get more complicated and will take advantage from the previous track training by storing and retrieving the car brains. By the end of this training, you will have created self-driving cars that are capable of driving on unknown tracks by understanding how to steer, accelerate, and brake based on what cars see in front of them. Since autonomous cars need a brain of some kind, you know we need some AI (artificial intelligence). AI comes in many forms, but in this guide, you’ll use a neural network where the weights are adjusted by a genetic algorithm. Employment opportunities often come from work samples and concrete skills, rather than a college degree. So, you need to learn the practical aspect well enough. This guide will not only help you learn well and build a stunning portfolio, it will also provide you continuous help and support. With this book and my dedicated 24/7 help and support team, there’s nothing for you to fear. I have helped many Python developers update their automation development skills, launch successful careers and get hired for remote jobs. I notice that even the most ambitious beginners can run into problems, such as unable to decide where to begin. Sometimes they get completely lost on the way and therefore need further help. In Chapter 13, I explain how to download my repository which contains all updates of the Python scripts (codes) and simulations used in this Part 2 of the guide. Although I explain all the codes used in this guide clearly, if you need further help, just use my support link at the end of the Chapter. The truth is everyone needs help at one point or the other to learn and build automation in their development journey. I can give you more challenges and their solutions in my subsequent trainings.
Author: Bolakale Aremu
Publisher: AB Publisher LLC
ISBN:
Category : Computers
Languages : en
Pages : 93
Get Book Here
Book Description
This is part 2 of my 3-part training guide on how to build self-driving cars from scratch. This guide is bundled with a repository containing simulations, python scripts, graphics, and other useful assets. In this step-by-step guide, I teach you how to make an app that you can use to create a simulation where cars learn how to drive autonomously over racing tracks. Here’s a break down of the contents of this guide. Part 1: Car mechanics. In this part, you’ll learn how to draw the car and control it with the keyboard. You will use a multimedia library for Python called Pyglet. (https://pyglet.org/). This is the only library you will use in this guide. This is a cross-platform windowing and multimedia library for Python. It’s a powerful yet easy-to-use Python library for building games and other visually rich applications on Windows, macOS, and Linux. Part 2:Neural network and genetic algorithm. You’ll learn how to create the AI where you combine a neural network and genetic algorithm. You’ll learn how to add sensors to the car and get output from them. To prevent the untrained network from car crashes, a genetic algorithm will be used to train the cars. This will help the cars to drive simple tracks. Part 3: Challenges. You’ll add some challenges to the system. Tracks get more complicated and will take advantage from the previous track training by storing and retrieving the car brains. By the end of this training, you will have created self-driving cars that are capable of driving on unknown tracks by understanding how to steer, accelerate, and brake based on what cars see in front of them. Since autonomous cars need a brain of some kind, you know we need some AI (artificial intelligence). AI comes in many forms, but in this guide, you’ll use a neural network where the weights are adjusted by a genetic algorithm. Employment opportunities often come from work samples and concrete skills, rather than a college degree. So, you need to learn the practical aspect well enough. This guide will not only help you learn well and build a stunning portfolio, it will also provide you continuous help and support. With this book and my dedicated 24/7 help and support team, there’s nothing for you to fear. I have helped many Python developers update their automation development skills, launch successful careers and get hired for remote jobs. I notice that even the most ambitious beginners can run into problems, such as unable to decide where to begin. Sometimes they get completely lost on the way and therefore need further help. In Chapter 13, I explain how to download my repository which contains all updates of the Python scripts (codes) and simulations used in this Part 2 of the guide. Although I explain all the codes used in this guide clearly, if you need further help, just use my support link at the end of the Chapter. The truth is everyone needs help at one point or the other to learn and build automation in their development journey. I can give you more challenges and their solutions in my subsequent trainings.
Author: Bolakale Aremu
Publisher: AB Publisher LLC
ISBN:
Category : Computers
Languages : en
Pages : 46
Get Book Here
Book Description
This is part 1 of my 3-part training guide on how to build self-driving cars from scratch. This guide is bundled with a repository containing simulations, python scripts, graphics, and other useful assets. In this step-by-step guide, I’ll teach you how to make an app that you can use to create a simulation where cars learn how to drive autonomously over racing tracks. Here’s a break down of the contents of this guide. Part 1: Car mechanics. In this part, you’ll learn how to draw the car and control it with the keyboard. You will use a multimedia library for Python called Pyglet. This is the only library you will use in this guide. This is a cross-platform windowing and multimedia library for Python. It’s a powerful yet easy-to-use Python library for building games and other visually rich applications on Windows, macOS, and Linux. Part 2: Neural network and genetic algorithm. You’ll learn how to create the AI where you combine a neural network and genetic algorithm. You’ll learn how to add sensors to the car and get output from them. To prevent the untrained network from car crashes, a genetic algorithm will be used to train the cars. This will help the cars to drive simple tracks. Part 3: Challenges. You’ll add some challenges to the system. Tracks get more complicated and will take advantage from the previous track training by storing and retrieving the car brains. By the end of this training, you will have created self-driving cars that are capable of driving on unknown tracks by understanding how to steer, accelerate, and brake based on what cars see in front of them. Since autonomous cars need a brain of some kind, you know we need some AI (artificial intelligence). AI comes in many forms, but in this guide, you’ll use a neural network where the weights are adjusted by a genetic algorithm. Employment opportunities often come from work samples and concrete skills, rather than a college degree. So, you need to learn the practical aspect well enough. This guide will not only help you learn well and build a stunning portfolio, it will also provide you continuous help and support. With this book and my dedicated 24/7 help and support team, there’s nothing for you to fear. I have helped many Python developers update their automation development skills, launch successful careers and get hired for remote jobs. I notice that even the most ambitious beginners can run into problems, such as unable to decide where to begin. Sometimes they get completely lost on the way and therefore need further help. In Chapter 3, I explain how to download my repository which contains all updates of the Python scripts (codes) and simulations used in this guide. Although I explain all the codes used in this guide clearly, if you need further help, just use my support link at the end of the Chapter. The truth is everyone needs help at one point or the other to learn and build automation in their development journey. I can give you more challenges and their solutions in my subsequent trainings.
Author: Dagmar Cagáňová
Publisher: Springer
ISBN: 3319769987
Category : Technology & Engineering
Languages : en
Pages : 490
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Book Description
This book presents current developments in smart city research and application regarding the management of manufacturing systems, Industry 4.0, transportation, and business management. It suggests approaches to incorporating smart city innovations into manufacturing systems, with an eye towards competitiveness in a global environment. The same pro-innovative approach is then applied to business and cooperation management. The authors also present smart city transportation solutions including vehicle data processing/reporting system, mobile application for fleet managers, bus drivers, bus passengers and special applications for smart city buses like passenger counting system, IP cameras, GPS system etc. The goal of the book is to establish channels of communication and disseminate knowledge among researchers and professionals working on smart city research and application. Features contributions on a variety of topics related to smart cities from global researchers and professionals in a wide range of sectors; Presents topics relating to smart cities such as manufacturing, business, and transportation; Includes expanded selected papers from EAI International Conference on Management of Manufacturing Systems (MMS 2016), EAI Industry of Things and Future Technologies Conference – Mobility IoT 2016 and International Conference on Smart Electric Vehicles and Vehicular Ad-hoc NETworks (SEVNET).
Author: Dr Yash Paul Soni
Publisher: Visionary Book Writers
ISBN: 1312205733
Category : Computers
Languages : en
Pages : 375
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Book Description
Artificial intelligence (AI) is one of the most fascinating and impactful fields of science and engineering in the 21st century. It has the potential to transform every aspect of human life, from health care to education, from entertainment to security, from business to politics. But what is AI exactly? How does it work? What are its challenges and opportunities? And how can we use it responsibly and ethically? This book aims to answer these questions and more by providing a comprehensive and accessible introduction to AI for anyone who wants to learn about this exciting and important topic. The book covers the main concepts, methods, and applications of AI, with an emphasis on understanding the underlying principles and logic behind the algorithms and systems. The book also presents real-world examples and case studies that illustrate how AI can be used to solve various problems and create value in different domains.
Author: Dror Poleg
Publisher: Springer Nature
ISBN: 3030134466
Category : Business & Economics
Languages : en
Pages : 309
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Book Description
Technology is revolutionizing the way real estate is designed, operated, and valued. It is democratizing access to capital and information, changing the way tenants use space, and eroding the power of regulation. Billions of dollars are funding these new real estate technologies and operating models. Value is shifting away from the assets themselves toward those who understand the needs of specific end-users and can use technology to deliver comprehensive, on-demand solutions. With all of these developments, there is an urgent need for a resource that helps industry practitioners think differently about their investment, customers, and competition. Rethinking Real Estate answers that call. It explores the impact of technology on all asset types — from retail projects, through lodging and residential properties, to office buildings and industrial facilities. Based on the author’s two decades of experience working across four continents alongside the world’s leading real estate investors, as well as hundreds of conversations with start-up founders and venture capitalists, this book provides practitioners with key insights, methodologies, and practical strategies to identify risks, take advantage of emerging opportunities, evaluate new competitors, and transform their organization, project, venture, or career. Whether you are an investor, developer, operator, broker, lender, facility manager, designer, planner, or technology entrepreneur, this book will help you navigate the exciting period ahead.
Author: Scott Burk
Publisher: CRC Press
ISBN: 1000433994
Category : Business & Economics
Languages : en
Pages : 258
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Book Description
Up to 70% and even more of corporate Analytics Efforts fail!!! Even after these corporations have made very large investments, in time, talent, and money, in developing what they thought were good data and analytics programs. Why? Because the executives and decision makers and the entire analytics team have not considered the most important aspect of making these analytics efforts successful. In this Book II of "It’s All Analytics!" series, we describe two primary things: 1) What this "most important aspect" consists of, and 2) How to get this "most important aspect" at the center of the analytics effort and thus make your analytics program successful. This Book II in the series is divided into three main parts: Part I, Organizational Design for Success, discusses ....... The need for a complete company / organizational Alignment of the entire company and its analytics team for making its analytics successful. This means attention to the culture – the company culture culture!!! To be successful, the CEO’s and Decision Makers of a company / organization must be fully cognizant of the cultural focus on ‘establishing a center of excellence in analytics’. Simply, "culture – company culture" is the most important aspect of a successful analytics program. The focus must be on innovation, as this is needed by the analytics team to develop successful algorithms that will lead to greater company efficiency and increased profits. Part II, Data Design for Success, discusses ..... Data is the cornerstone of success with analytics. You can have the best analytics algorithms and models available, but if you do not have good data, efforts will at best be mediocre if not a complete failure. This Part II also goes further into data with descriptions of things like Volatile Data Memory Storage and Non-Volatile Data Memory Storage, in addition to things like data structures and data formats, plus considering things like Cluster Computing, Data Swamps, Muddy Data, Data Marts, Enterprise Data Warehouse, Data Reservoirs, and Analytic Sandboxes, and additionally Data Virtualization, Curated Data, Purchased Data, Nascent & Future Data, Supplemental Data, Meaningful Data, GIS (Geographic Information Systems) & Geo Analytics Data, Graph Databases, and Time Series Databases. Part II also considers Data Governance including Data Integrity, Data Security, Data Consistency, Data Confidence, Data Leakage, Data Distribution, and Data Literacy. Part III, Analytics Technology Design for Success, discusses .... Analytics Maturity and aspects of this maturity, like Exploratory Data Analysis, Data Preparation, Feature Engineering, Building Models, Model Evaluation, Model Selection, and Model Deployment. Part III also goes into the nuts and bolts of modern predictive analytics, discussing such terms as AI = Artificial Intelligence, Machine Learning, Deep Learning, and the more traditional aspects of analytics that feed into modern analytics like Statistics, Forecasting, Optimization, and Simulation. Part III also goes into how to Communicate and Act upon Analytics, which includes building a successful Analytics Culture within your company / organization. All-in-all, if your company or organization needs to be successful using analytics, this book will give you the basics of what you need to know to make it happen.
Author: Steven D. Peterson
Publisher: John Wiley & Sons
ISBN: 1119245494
Category : Business & Economics
Languages : en
Pages : 422
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Book Description
The fast and easy way to construct a winning business plan If you're looking to establish, expand, or re-energize a business, the best place to start is with a sound business plan—and this new edition of Business Plans Kit For Dummies is here to help you get you started. From getting your hands on start-up money from investors to successfully growing or reimaging your venture, it offers everything you need to craft a well-defined business plan that will set you on a course to get your business moving in the right direction. Are you unsure how to draft objectives for managers or deal with displacement? Are you new to hiring employees and need help grasping the ins and outs of creating a new business? No worries! Business Plans Kit For Dummies is brimming with all the tools and expert guidance you need to bring a successful business plan to life and keep your company afloat in any economic environment. Including the latest tips and resources, and packed with lots of helpful examples and sample forms, it offers everything you need to craft a winning business plan and increase the likelihood your business will not only survive, but thrive! Create a sound business plan and clear mission statement Establish and assess your goals and objectives Get start-up money in any economy Increase your business' chances of financial success If you're a small business owner, investor, or entrepreneur looking for expert guidance on developing and implementing a strategic plan to help your business succeed, Business Plans Kit For Dummies has you covered!
Author: Sumit Ranjan
Publisher: Packt Publishing Ltd
ISBN: 1838647023
Category : Computers
Languages : en
Pages : 320
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Book Description
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.
Author: Fritz Dufour, MBA, DESS
Publisher: Fritz Dufour
ISBN:
Category : Philosophy
Languages : en
Pages : 204
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Book Description
The difference between Part I and Part II – Volumes 1 & 2 – of this series, is that in Part I the author showed how what we call reality starts with the inner self whereas Part II describes what, in fact, impacts and modifies the environment or reality and what are the factors behind that dynamics. What impacts and modifies the environment is science. This Volume 2 starts by showing how technology plays an important role in scientific progress. Although the relationship between the two is symbiotic, science can exist without technology but technology desperately needs science. Military technology is an example of how technology can help science advance. Some military inventions end up having civilian use. Science being at the center of society, the book makes the case for the direct impact of such social sciences as politics and economics on the advancement of science. Politics, says the author, influences science because of uncertainty in science, and economics does it thanks to the availability of money to scholars and scientists for their research. On the other hand, government also influences scientific progress through regulations. The book gives cyberspace regulation as an example. Furthermore, by showing how art influences science, the author really argues for the polyfactorial aspect of scientific progress. In that line of thought, he goes on to also prove that factors such as skepticism, curiosity, and the quest for knowledge greatly influence the advancement of science. That, says the author, “is a ninety-degree turn … By ending Part two that way, I wanted to, somehow, link it to Part I, which argues that reality starts from within.”
Author: Hod Lipson
Publisher: MIT Press
ISBN: 0262035227
Category : Architecture
Languages : en
Pages : 324
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Book Description
When human drivers let intelligent software take the wheel: the beginning of a new era in personal mobility.
