Build smart applications by implementing real-world artificial intelligence projects
Key Features
*Explore a variety of AI projects with Python
*Get well-versed with different types of neural networks and popular deep learning algorithms
*Leverage popular Python deep learning libraries for your AI projects
Book Description
Artificial Intelligence (AI) is the newest technology that’s being…
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Author : Dr. Joshua Eckroth
Genre : Computers
Summary : Build smart applications by implementing real-world artificial intelligence projects Key Features Explore a variety of AI projects with Python Get well-versed with different types of neural networks and popular deep learning algorithms Leverage popular Python deep learning libraries for your AI projects Book Description Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence. This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library. By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress What you will learn Build a prediction model using decision trees and random forest Use neural networks, decision trees, and random forests for classification Detect YouTube comment spam with a bag-of-words and random forests Identify handwritten mathematical symbols with convolutional neural networks Revise the bird species identifier to use images Learn to detect positive and negative sentiment in user reviews Who this book is for Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you’re able to play around with code
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Author : Prateek Joshi
Genre : Computers
Summary : 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.
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Author : Ben Coppin
Genre : Computers
Summary : Artificial Intelligence Illuminated presents an overview of the background and history of artificial intelligence, emphasizing its importance in today's society and potential for the future. The book covers a range of AI techniques, algorithms, and methodologies, including game playing, intelligent agents, machine learning, genetic algorithms, and Artificial Life. Material is presented in a lively and accessible manner and the author focuses on explaining how AI techniques relate to and are derived from natural systems, such as the human brain and evolution, and explaining how the artificial equivalents are used in the real world. Each chapter includes student exercises and review questions, and a detailed glossary at the end of the book defines important terms and concepts highlighted throughout the text.
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Author : Alberto Artasanchez
Genre : Computers
Summary : 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.
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Author : Ai Publishing
Genre :
Summary : Python Machine Learning for BeginnersMachine Learning (ML) and Artificial Intelligence (AI) are here to stay. Yes, that's right. Based on a significant amount of data and evidence, it's obvious that ML and AI are here to stay.Consider any industry today. The practical applications of ML are really driving business results. Whether it's healthcare, e-commerce, government, transportation, social media sites, financial services, manufacturing, oil and gas, marketing and salesYou name it. The list goes on. There's no doubt that ML is going to play a decisive role in every domain in the future.But what does a Machine Learning professional do?A Machine Learning specialist develops intelligent algorithms that learn from data and also adapt to the data quickly. Then, these high-end algorithms make accurate predictions. Python Machine Learning for Beginners presents you with a hands-on approach to learn ML fast.How Is This Book Different?AI Publishing strongly believes in learning by doing methodology. With this in mind, we have crafted this book with care. You will find that the emphasis on the theoretical aspects of machine learning is equal to the emphasis on the practical aspects of the subject matter.You'll learn about data analysis and visualization in great detail in the first half of the book. Then, in the second half, you'll learn about machine learning and statistical models for data science.Each chapter presents you with the theoretical framework behind the different data science and machine learning techniques, and practical examples illustrate the working of these techniques.When you buy this book, your learning journey becomes so much easier. The reason is you get instant access to all the related learning material presented with this book--references, PDFs, Python codes, and exercises--on the publisher's website. All this material is available to you at no extra cost. You can download the ML datasets used in this book at runtime, or you can access them via the Resources/Datasets folder.You'll also find the short course on Python programming in the second chapter immensely useful, especially if you are new to Python. Since this book gives you access to all the Python codes and datasets, you only need access to a computer with the internet to get started. The topics covered include: Introduction and Environment Setup Python Crash Course Python NumPy Library for Data Analysis Introduction to Pandas Library for Data Analysis Data Visualization via Matplotlib, Seaborn, and Pandas Libraries Solving Regression Problems in ML Using Sklearn Library Solving Classification Problems in ML Using Sklearn Library Data Clustering with ML Using Sklearn Library Deep Learning with Python TensorFlow 2.0 Dimensionality Reduction with PCA and LDA Using Sklearn Click the BUY NOW button to start your Machine Learning journey.
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Author : AI OÜ
Genre :
Summary : A practical guide to machine learning with Python through the presentation and guided completion of ten real-world projects Key Features Step-by-step roadmap to data science and machine learning A Python crash course in machine learning 10 machine learning and data science projects for practical study Book Description Machine Learning (ML) is the lifeblood of businesses worldwide. ML tools empower organizations to identify profitable opportunities fast and help them to better understand potential risks. The ever-expanding data, cost-effective data storage, and competitively priced powerful processing continue to drive the growth of ML. This is the best time you could enter the exciting machine learning universe. Industries are reinventing themselves constantly by developing more advanced data analysis models. These models analyze larger and more complex data than ever while delivering instantaneous and more accurate results on enormous scales. In this backdrop, it is evident that hands-on practice is everything in machine learning. Tons of theory will amount to nothing if you don't have enough hands-on practice. Textbooks and online classes mislead you into a false sense of mastery. The easy availability of learning resources tricks you and you become overconfident. But when you try to apply the theoretical concepts you have learned, you realize it's not that simple. This is where projects play a crucial role in your learning journey. Projects are doubtless the best investment of your time. You'll not only enjoy learning but you'll also make quick progress. And unlike studying boring theoretical concepts, you'll find that working on projects is easier to stay motivated. The projects in this book cover ten different interesting topics. Each project will help you refine your ML skills and apply them in the real world. These projects also present you with an opportunity to enrich your portfolio, making it simpler to find a great job, explore interesting career paths, and even negotiate a higher pay package. Overall, this learning-by-doing book will help you accomplish your machine learning career goals faster. The code bundle for this course is available at https://www.aispublishing.net/ai-sciences-book What you will learn House price prediction using linear regression Filtering spam email messages using Naive Bayes algorithm Predicting used car sale price using Feedforward Artificial Neural Networks Predicting stock market trends with RNN (LSTM)...
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Author : Ai Publishing
Genre :
Summary : **GET YOUR COPY NOW, the price will be 19.99$ soon**Learn and Build Deep Learning Models Today !Welcome to the Deep Learning with Python Book!The book offers you a solid introduction to the world of artificial intelligence. In this program, you'll master fundamentals that will enable you to go further in the field, launch or advance a career, and join the next generation of deep learning talent that will help define a beneficial, new, AI-powered future for our world. You will study cutting-edge topics such as Machine learning, Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and build projects in keras and TensorFlow. You'll learn from our AI Experts. The Book is comprised of 5 projects. Each project you build will be an opportunity to prove your skills and demonstrate what you've learned in your lessons. Building a project is one of the best ways both to test the skills you've acquired and to demonstrate your newfound abilities to future employers. Educational Objectives: Become an expert in neural networks, and learn to implement them from scratch and using frameworks like Keras and TensorFlow. Prerequisite Knowledge: Make sure to set aside adequate time on your calendar for focused Learn. In order to succeed in this book. Contact Info: While going through the program, if you have questions about anything, you can reach us at contact@aispublishing.net. **GET YOUR COPY NOW, the price will be 12.99$ soon**What's Inside This Book? Project 0: Introduction to Python for AI Project 1: Introduction to Keras and OpenCV Project 2: Simple Linear Regression in Python Project 3: Multivariate Regression in Python Project 4: Binary Classification for image recognition using CNN Project 5: Multiclass Classification for image recognition using CNN Project 6: d104 Classification using RNN ** MONEY BACK GUARANTEE BY AMAZON **If you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform or contact us by sending an email at contact@aispublishing.net.**GET YOUR COPY NOW, the price will be 12.99$ soon**
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Author : Sebastian Raschka
Genre : Computers
Summary : Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
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Author : Lisa Tagliaferri
Genre : Computers
Summary : As machine learning is increasingly leveraged to find patterns, conduct analysis, and make decisions — sometimes without final input from humans who may be impacted by these findings — it is crucial to invest in bringing more stakeholders into the fold. This book of Python projects in machine learning tries to do just that: to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning to help ensure that it is serving us all. This book will set you up with a Python programming environment if you don’t have one already, then provide you with a conceptual understanding of machine learning in the chapter “An Introduction to Machine Learning.” What follows next are three Python machine learning projects. They will help you create a machine learning classifier, build a neural network to recognize handwritten digits, and give you a background in deep reinforcement learning through building a bot for Atari.
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Author : Willard D Sanders
Genre :
Summary : Are you one of those people who wish to master machine learning with Python? Perhaps you like to learn the vital tools novices must learn about Python programming. Congratulations, because you've come to the perfect place! In this book bundle, Python: 2 Books In 1 Learn Python Programming for Beginners + Python Machine Learning, you will get the methods, which will support you to finish your projects efficiently and effectively like a pro. Today is the perfect time to learn how to experiment with new concepts and learn problem-solving, boost your programming skills, but above all, enhance your confidence. You see, creativity and imagination will open new doors to your project that you never imagined possible. Here's a quick peek of what you'll find inside: Book 1: Learn Python Programming For Beginners: A Beginner's Guide To Comprehending Python. Develop Your Programming Skills And Learn All The Tricks With This Crash Course. What is Python Advantages and disadvantages Python installation Learning python from scratch Book 2: PYTHON MACHINE LEARNING: The Complete Beginner's Guide To Deep Learning With Python. Learn To Use Scikit-Learn And Pandas What is machine learning Artificial intelligence and deep learning Supervised learning vs unsupervised learning How to apply machine learning in the world Python for machine learning The main libraries to start machine learning and what they are for Allow this book bundle to enlighten you on what goes into Python programming that works. There's no need to hesitate. It's time to get to know Python Machine Learning and Programming and begin your journey towards success. Grab your copy and explore many brain-boosting concepts inside. That's especially true if you are tired of time-consuming and failed projects in the past. Are you ready? Scroll up this page and click BUY NOW!