Artificial Intelligence With Python Complete Self Assessment Guide

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Artificial Intelligence With Python Complete Self Assessment Guide

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Author : Gerardus Blokdyk
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-07-25

Artificial Intelligence With Python Complete Self Assessment Guide written by Gerardus Blokdyk and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-25 with categories.

Risk factors: what are the characteristics of Artificial Intelligence with Python that make it risky? How can we incorporate support to ensure safe and effective use of Artificial Intelligence with Python into the services that we provide? What potential environmental factors impact the Artificial Intelligence with Python effort? What knowledge, skills and characteristics mark a good Artificial Intelligence with Python project manager? What other jobs or tasks affect the performance of the steps in the Artificial Intelligence with Python process? Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role... In EVERY company, organization and department. Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' For more than twenty years, The Art of Service's Self-Assessments empower people who can do just that - whether their title is marketer, entrepreneur, manager, salesperson, consultant, business process manager, executive assistant, IT Manager, CxO etc... - they are the people who rule the future. They are people who watch the process as it happens, and ask the right questions to make the process work better. This book is for managers, advisors, consultants, specialists, professionals and anyone interested in Artificial Intelligence with Python assessment. All the tools you need to an in-depth Artificial Intelligence with Python Self-Assessment. Featuring 615 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Artificial Intelligence with Python improvements can be made. In using the questions you will be better able to: - diagnose Artificial Intelligence with Python projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Artificial Intelligence with Python and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Artificial Intelligence with Python Scorecard, you will develop a clear picture of which Artificial Intelligence with Python areas need attention. Included with your purchase of the book is the Artificial Intelligence with Python Self-Assessment downloadable resource, which contains all questions and Self-Assessment areas of this book in a ready to use Excel dashboard, including the self-assessment, graphic insights, and project planning automation - all with examples to get you started with the assessment right away. Access instructions can be found in the book. You are free to use the Self-Assessment contents in your presentations and materials for customers without asking us - we are here to help.

Artificial Intelligence With Python Complete Self Assessment Guide

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Author : Gerardus Blokdyk
language : en
Publisher: 5starcooks
Release Date : 2018-01-05

Artificial Intelligence With Python Complete Self Assessment Guide written by Gerardus Blokdyk and has been published by 5starcooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-05 with categories.

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Artificial Intelligence With Python

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Author : Alberto Artasanchez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31

Artificial Intelligence With Python written by Alberto Artasanchez and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Computers categories.

New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.

Machine Learning Automation With Tpot

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Author : Dario Radecic
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-05-07

Machine Learning Automation With Tpot written by Dario Radecic and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-07 with Computers categories.

Discover how TPOT can be used to handle automation in machine learning and explore the different types of tasks that TPOT can automate Key FeaturesUnderstand parallelism and how to achieve it in Python.Learn how to use neurons, layers, and activation functions and structure an artificial neural network.Tune TPOT models to ensure optimum performance on previously unseen data.Book Description The automation of machine learning tasks allows developers more time to focus on the usability and reactivity of the software powered by machine learning models. TPOT is a Python automated machine learning tool used for optimizing machine learning pipelines using genetic programming. Automating machine learning with TPOT enables individuals and companies to develop production-ready machine learning models cheaper and faster than with traditional methods. With this practical guide to AutoML, developers working with Python on machine learning tasks will be able to put their knowledge to work and become productive quickly. You'll adopt a hands-on approach to learning the implementation of AutoML and associated methodologies. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will show you how to build automated classification and regression models and compare their performance to custom-built models. As you advance, you'll also develop state-of-the-art models using only a couple of lines of code and see how those models outperform all of your previous models on the same datasets. By the end of this book, you'll have gained the confidence to implement AutoML techniques in your organization on a production level. What you will learnGet to grips with building automated machine learning modelsBuild classification and regression models with impressive accuracy in a short timeDevelop neural network classifiers with AutoML techniquesCompare AutoML models with traditional, manually developed models on the same datasetsCreate robust, production-ready modelsEvaluate automated classification models based on metrics such as accuracy, recall, precision, and f1-scoreGet hands-on with deployment using Flask-RESTful on localhostWho this book is for Data scientists, data analysts, and software developers who are new to machine learning and want to use it in their applications will find this book useful. This book is also for business users looking to automate business tasks with machine learning. Working knowledge of the Python programming language and beginner-level understanding of machine learning are necessary to get started.

Python Beginner S Guide To Artificial Intelligence

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Author : Denis Rothman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-24

Python Beginner S Guide To Artificial Intelligence written by Denis Rothman and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-24 with Computers categories.

This Learning Path offers practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. You will be introduced to various machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and ...

Learn Python From An Expert The Complete Guide With Artificial Intelligence

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Author : Edson L P Camacho
language : en
Publisher:
Release Date : 2023-06-08

Learn Python From An Expert The Complete Guide With Artificial Intelligence written by Edson L P Camacho and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-08 with Computers categories.

The Ultimate Guide to Advanced Python and Artificial Intelligence: Unleash the Power of Code! Are you ready to take your Python programming skills to the next level and dive into the exciting world of artificial intelligence? Look no further! We proudly present the comprehensive book written by renowned author Edson L P Camacho: "Advanced Python: Mastering AI." In today's rapidly evolving technological landscape, the demand for AI professionals is soaring. Python, with its simplicity and versatility, has become the go-to language for AI development. Whether you are a seasoned Pythonista or a beginner eager to learn, this book is your gateway to mastering AI concepts and enhancing your programming expertise. What sets "Advanced Python: Mastering AI" apart from other books is its unparalleled combination of in-depth theory and hands-on practicality. Edson L P Camacho, a leading expert in the field, guides you through every step, from laying the foundation of Python fundamentals to implementing cutting-edge AI algorithms. Here's a glimpse of what you'll find within the pages of this comprehensive guide: 1. Python Fundamentals: Review and reinforce your knowledge of Python basics, including data types, control flow, functions, and object-oriented programming. Build a solid foundation to tackle complex AI concepts. 2. Data Manipulation and Visualization: Learn powerful libraries such as NumPy, Pandas, and Matplotlib to handle and analyze data. Understand how to preprocess and visualize data effectively for AI applications. 3. Machine Learning Essentials: Dive into the world of machine learning and explore popular algorithms like linear regression, decision trees, support vector machines, and neural networks. Discover how to train, evaluate, and optimize models for various tasks. 4. Deep Learning and Neural Networks: Delve deeper into neural networks, the backbone of modern AI. Gain insights into deep learning architectures, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Implement advanced techniques like transfer learning and generative models. 5. Natural Language Processing (NLP): Explore the fascinating field of NLP and learn how to process and analyze textual data using Python. Discover techniques like sentiment analysis, named entity recognition, and text generation. 6. Computer Vision: Unleash the power of Python for image and video analysis. Build computer vision applications using popular libraries like OpenCV and TensorFlow. Understand concepts like object detection, image segmentation, and image captioning. 7. Reinforcement Learning: Embark on the exciting journey of reinforcement learning. Master the fundamentals of Q-learning, policy gradients, and deep Q-networks. Create intelligent agents that can learn and make decisions in dynamic environments. "Advanced Python: Mastering AI" not only equips you with the theoretical knowledge but also provides numerous real-world examples and projects to reinforce your understanding. Each chapter is accompanied by practical exercises and coding challenges to sharpen your skills and boost your confidence. Don't miss the opportunity to stay ahead in this AI-driven era. Order your copy of "Advanced Python: Mastering AI" today and unlock the full potential of Python programming with artificial intelligence. Take your career to new heights and become a proficient AI developer. Get ready to write the code that shapes the future!

A Practical Guide To Artificial Intelligence And Data Analytics

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Author : Rayan Wali
language : en
Publisher: Rayan Wali
Release Date : 2021-06-12

A Practical Guide To Artificial Intelligence And Data Analytics written by Rayan Wali and has been published by Rayan Wali this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-12 with Computers categories.

Whether you are looking to prepare for AI/ML/Data Science job interviews or you are a beginner in the field of Data Science and AI, this book is designed for engineers and AI enthusiasts like you at all skill levels. Taking a different approach from a traditional textbook style of instruction, A Practical Guide to AI and Data Analytics touches on all of the fundamental topics you will need to understand deeper into machine learning and artificial intelligence research, literature, and practical applications with its four parts: Part I: Concept Instruction Part II: 8 Full-Length Case Studies Part III: 50+ Mixed Exercises Part IV: A Full-Length Assessment With an illustrative approach to instruction, worked examples, and case studies, this easy-to-understand book simplifies many of the AI and Data Analytics key concepts, leading to an improvement of AI/ML system design skills.

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide

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Author : Mona Mona
language : en
Publisher: John Wiley & Sons
Release Date : 2023-10-27

Official Google Cloud Certified Professional Machine Learning Engineer Study Guide written by Mona Mona and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-27 with Computers categories.

Expert, guidance for the Google Cloud Machine Learning certification exam In Google Cloud Certified Professional Machine Learning Study Guide, a team of accomplished artificial intelligence (AI) and machine learning (ML) specialists delivers an expert roadmap to AI and ML on the Google Cloud Platform based on new exam curriculum. With Sybex, you’ll prepare faster and smarter for the Google Cloud Certified Professional Machine Learning Engineer exam and get ready to hit the ground running on your first day at your new job as an ML engineer. The book walks readers through the machine learning process from start to finish, starting with data, feature engineering, model training, and deployment on Google Cloud. It also discusses best practices on when to pick a custom model vs AutoML or pretrained models with Vertex AI platform. All technologies such as Tensorflow, Kubeflow, and Vertex AI are presented by way of real-world scenarios to help you apply the theory to practical examples and show you how IT professionals design, build, and operate secure ML cloud environments. The book also shows you how to: Frame ML problems and architect ML solutions from scratch Banish test anxiety by verifying and checking your progress with built-in self-assessments and other practical tools Use the Sybex online practice environment, complete with practice questions and explanations, a glossary, objective maps, and flash cards A can’t-miss resource for everyone preparing for the Google Cloud Certified Professional Machine Learning certification exam, or for a new career in ML powered by the Google Cloud Platform, this Sybex Study Guide has everything you need to take the next step in your career.

Artificial Intelligence For Robotics

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Author : Francis X. Govers III
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29

Artificial Intelligence For Robotics written by Francis X. Govers III and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Technology & Engineering categories.

Learn how to apply artificial intelligence, engineering, and machine learning to create smart robots capable of interacting with their environment, engaging with users, making decisions, and navigating autonomously Key Features Gain a holistic understanding of robot design, systems engineering, and task analysis Implement AI/ML techniques to detect and manipulate objects and navigate robots using landmarks Integrate voice and natural language interactions to create a digital assistant and artificial personality for your robot Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionUnlock the potential of your robots by enhancing their perception with cutting-edge artificial intelligence and machine learning techniques. From neural networks to computer vision, this book equips you with the tools and practical use cases to create truly smart robots. Starting with robotics basics, robot architecture, control systems, and decision-making theory, this book presents systems-engineering methods to design problem-solving robots with single-board computers. You’ll explore object recognition and genetic algorithms to teach your robot to identify and pick up objects, and you'll also harness the power of natural language processing to give your robot a voice. To enhance your robot further, you’ll master neural networks to classify and separate objects and navigate autonomously, before advancing to guiding your robot arms using reinforcement learning and genetic algorithms. The book also covers path planning and goal-oriented programming to prioritize your robot's tasks, showing you how to connect all software using Python and ROS 2 for a seamless experience. By the end of this book, you’ll have learned how to transform your robot into a helpful assistant with NLP and give it an artificial personality, ready to tackle real-world tasks and even crack jokes.What you will learn Get started with robotics and AI essentials Understand path planning, decision trees, and search algorithms to enhance your robot Explore object recognition using neural networks and supervised learning techniques Employ genetic algorithms to enable your robot arm to manipulate objects Teach your robot to listen using Natural Language Processing through an expert system Program your robot in how to avoid obstacles and retrieve objects with machine learning and computer vision Apply simulation techniques to give your robot an artificial personality Who this book is for This book is for practicing robotics engineers and enthusiasts aiming to advance their skills by applying AI and ML techniques. Students and researchers looking for practical guidance for solving specific problems or approaching a difficult robot design will find this book insightful. Proficiency in Python programming, familiarity with electronics and wiring, single board computers, Linux-based command-line interface (CLI), and knowledge of AI/ML concepts are required to get started with this book.

Modern Data Mining With Python

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Author : Dushyant Singh Sengar
language : en
Publisher: BPB Publications
Release Date : 2024-02-26

Modern Data Mining With Python written by Dushyant Singh Sengar and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-26 with Computers categories.

Data miner’s survival kit for explainable, effective, and efficient algorithms enabling responsible decision-making KEY FEATURES ● Accessible, and case-based exploration of the most effective data mining techniques in Python. ● An indispensable guide for utilizing AI potential responsibly. ● Actionable insights on modeling techniques, deployment technologies, business needs, and the art of data science, for risk mitigation and better business outcomes. DESCRIPTION "Modern Data Mining with Python" is a guidebook for responsibly implementing data mining techniques that involve collecting, storing, and analyzing large amounts of structured and unstructured data to extract useful insights and patterns. Enter into the world of data mining and machine learning. Use insights from various data sources, from social media to credit card transactions. Master statistical tools, explore data trends, and patterns. Understand decision trees and artificial neural networks (ANNs). Manage high-dimensional data with dimensionality reduction. Explore binary classification with logistic regression. Spot concealed patterns with unsupervised learning. Analyze text with recurrent neural networks (RNNs) and visuals with convolutional neural networks (CNNs). Ensure model compliance with regulatory standards. After reading this book, readers will be equipped with the skills and knowledge necessary to use Python for data mining and analysis in an industry set-up. They will be able to analyze and implement algorithms on large structured and unstructured datasets. WHAT YOU WILL LEARN ● Explore the data mining spectrum ranging from data exploration and statistics. ● Gain hands-on experience applying modern algorithms to real-world problems in the financial industry. ● Develop an understanding of various risks associated with model usage in regulated industries. ● Gain knowledge about best practices and regulatory guidelines to mitigate model usage-related risk in key banking areas. ● Develop and deploy risk-mitigated algorithms on self-serve ModelOps platforms. WHO THIS BOOK IS FOR This book is for a wide range of early career professionals and students interested in data mining or data science with a financial services industry focus. Senior industry professionals, and educators, trying to implement data mining algorithms can benefit as well. TABLE OF CONTENTS 1. Understanding Data Mining in a Nutshell 2. Basic Statistics and Exploratory Data Analysis 3. Digging into Linear Regression 4. Exploring Logistic Regression 5. Decision Trees with Bagging and Boosting 6. Support Vector Machines and K-Nearest Neighbors 7. Putting Dimensionality Reduction into Action 8. Beginning with Unsupervised Models 9. Structured Data Classification using Artificial Neural Networks 10. Language Modeling with Recurrent Neural Networks 11. Image Processing with Convolutional Neural Networks 12. Understanding Model Risk Management for Data Mining Models 13. Adopting ModelOps to Manage Model Risk