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Author: Giuseppe Bonaccorso
Publisher: Packt Publishing Ltd
ISBN: 1789951720
Category : Computers
Languages : en
Pages : 748
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Book Description
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key FeaturesMaster supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and moreBuild, deploy, and scale end-to-end deep neural network models in a production environmentBook Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: Mastering Machine Learning Algorithms by Giuseppe BonaccorsoMastering TensorFlow 1.x by Armando FandangoDeep Learning for Computer Vision by Rajalingappaa ShanmugamaniWhat you will learnExplore how an ML model can be trained, optimized, and evaluatedWork with Autoencoders and Generative Adversarial NetworksExplore the most important Reinforcement Learning techniquesBuild end-to-end deep learning (CNN, RNN, and Autoencoders) modelsWho this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.
Author: Giuseppe Bonaccorso
Publisher: Packt Publishing Ltd
ISBN: 1789951720
Category : Computers
Languages : en
Pages : 748
Get Book
Book Description
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key FeaturesMaster supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and moreBuild, deploy, and scale end-to-end deep neural network models in a production environmentBook Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: Mastering Machine Learning Algorithms by Giuseppe BonaccorsoMastering TensorFlow 1.x by Armando FandangoDeep Learning for Computer Vision by Rajalingappaa ShanmugamaniWhat you will learnExplore how an ML model can be trained, optimized, and evaluatedWork with Autoencoders and Generative Adversarial NetworksExplore the most important Reinforcement Learning techniquesBuild end-to-end deep learning (CNN, RNN, and Autoencoders) modelsWho this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.
Author: Giuseppe Bonaccorso
Publisher:
ISBN: 9781789957211
Category : Computers
Languages : en
Pages : 764
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Book Description
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and more Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: Mastering Machine Learning Algorithms by Giuseppe Bonaccorso Mastering TensorFlow 1.x by Armando Fandango Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn Explore how an ML model can be trained, optimized, and evaluated Work with Autoencoders and Generative Adversarial Networks Explore the most important Reinforcement Learning techniques Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.
Author: Edson L P Camacho
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 620
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Book Description
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!
Author: Prateek Joshi
Publisher: Packt Publishing Ltd
ISBN: 1786469677
Category : Computers
Languages : en
Pages : 437
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Book Description
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.
Author: Alberto Artasanchez
Publisher: Packt Publishing Ltd
ISBN: 1839216077
Category : Computers
Languages : en
Pages : 619
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Book Description
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.
Author: Russel R Russo
Publisher:
ISBN: 9781709584336
Category :
Languages : en
Pages : 196
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Book Description
Are you fascinated by Machine Learning but it seems too complicated?Do you have some coding skills but you want to go deeper in Python and Machine Learning? If this is you, please keep reading: you are in the right place, looking at the right book. Since you are reading this you are probably aware of how important Artificial Intelligence is in these days. In your everyday life Artificial Intelligence is all around you. Every time you buy a product on Amazon, follow a new profile on Instagram, listen to a song on Spotify or reserve a room on Booking, they are learning something out of your behavior. And these are just the most visible aspects of how Machine Learning is having an impact on our lives. Everyone knows (well, almost everyone) how important Machine Learning is for the growth and success of the biggest tech companies, and many people know about the Machine Learning impact in science, medicine and statistics. Also, it is quite commonly known that Artificial Intelligence, Machine Learning, and the mastering of their most important language, Python, can offer a lot of possibilities in work and business. And you yourself are probably thinking "I surely can see that opportunity, but how can I seize it?" Well, if you kept reading so far you are on the right track to answer your question. In Machine Learning with Python you will find: Why python is the best language for Machine Learning How to bring your ideas into a computer The smartest way to approach Machine Learning How to deal with variables and data Tips and tricks for a smooth and painless journey into artificial intelligence The most common myths about Machine Learning debunked So, whether you decided to start now or to go deeper into Artificial Intelligence, Machine Learning and Python Programming, you will only have two unanswered questions right now: "what is the best way to do it? And when is the best time to start?" An easy, clear and complete guide as Machine Learning with Python is the answer to your first question, and about the second one, well, that's an easy one: the best time is NOW! Download Machine Learning with Python now and start mastering the secrets of Artificial Intelligence.Scroll to the top of the page and click the BUY NOW button.
Author: Paige Jacobs
Publisher:
ISBN: 9781675391457
Category :
Languages : en
Pages : 230
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Book Description
Learning is a crucial factor in intelligence. The realization of intelligent systems by computers, which are not programmed but trained, is the goal of Artificial Intelligence. Machine learning deals with the necessary methods and algorithms to provide artificial intelligence. These formulate different learning objectives, address diverse application areas, and make different demands on existing data.Anyone who wants to intelligently use more substantial amounts of data to generate added value from them needs an overview of machine learning. On the other hand, a deeper algorithmic understanding is required to estimate effort and to increase success rates through adjustments. The aim of the book is, therefore, to make learners fit for machine learning (theoretical and practical). We will work with Python and related libraries offering open-source and state-of-the-art implementations. Also, we look at aspects of machine learning in the cloud with concrete examples.The "Advanced Machine Learning with Python" teaches the formalization of learning problems, methods for dimensionality reduction and input engineering as well as ensemble methods. Participants will be familiar with the Python Machine Learning tools following the training.Machine learning, as part of artificial intelligence, is about using the right features to construct the right models for solving a specific task. Models are nothing more than the output of algorithms applied to the data.We learn which algorithms exist for which tasks and how we can use them with Scikit-learn in Python. We'll go through advanced aspects, such as scalability of solutions and the combination of models, as well as discussing deep learning, currently the hottest topic in machine learning.Machine learning doesn't work for any particular industry; instead, it works in virtually all of them in some way. We have aimed the further education module at all those who are already analyzing data or would like to do more in the future and would like to acquire more competences. If you want to understand how Python can help answer critical questions about your data, you've come to the right place. Whether you are a beginner or want to deepen your knowledge in the field of data science, this book is an indispensable source of information and well worth the time it will take to read. Now is your chance to advance your knowledge of machine learning with the use of Python. What are you waiting for? Get started now!
Author: John Hearty
Publisher: Packt Publishing Ltd
ISBN: 1784393835
Category : Computers
Languages : en
Pages : 278
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Book Description
Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python About This Book Resolve complex machine learning problems and explore deep learning Learn to use Python code for implementing a range of machine learning algorithms and techniques A practical tutorial that tackles real-world computing problems through a rigorous and effective approach Who This Book Is For This title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you! Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful. What You Will Learn Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Apply your new found skills to solve real problems, through clearly-explained code for every technique and test Automate large sets of complex data and overcome time-consuming practical challenges Improve the accuracy of models and your existing input data using powerful feature engineering techniques Use multiple learning techniques together to improve the consistency of results Understand the hidden structure of datasets using a range of unsupervised techniques Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models together In Detail Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data. The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce. This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano. By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering. Style and approach This book focuses on clarifying the theory and code behind complex algorithms to make them practical, useable, and well-understood. Each topic is described with real-world applications, providing both broad contextual coverage and detailed guidance.
Author: Benjamin Smith
Publisher:
ISBN:
Category :
Languages : en
Pages : 230
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Book Description
Are you interested in taking your deep learning knowledge to the next level? Then this is the book for you! Machine and deep learning are the future, and there's no getting away from that. So learning it now, and learning how to do it the right way will put you ahead of the crowd. Deep learning is all about understanding and learning about neural networks, and Python is the best computer programming language to do that with. Learning to program is not easy, but consistent practice is the key. Learning to program efficiently in Python and building deep learning neural networks becomes simple to do with practice and guidance.In this book, you will learn: -The basics of the Python programming language-All about variables, strings, classes, statements, dictionaries, functions, and more-What Artificial Intelligence is-What Deep Learning is-How to build a deep neural network with Keras-How to build a deep learning convolutional neural network-The practical applications of deep learning-The benefits and the drawbacks of deep learningAnd so much more!Don't delay. Start your advanced deep learning journey today by clicking the Buy Now button!
Author: Hacktech Academy
Publisher:
ISBN: 9781802350357
Category :
Languages : en
Pages : 112
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Book Description
⭐️ 55% OFF for Bookstores! NOW at $ 34.95 instead of $ 54.19 ⭐️ Do you want to Master Python Programming? Then You Are 1-Click Away to make your customers Learning Why Python Is The Preferred Programming Language In Computer Science, Big Data, Machine Learning, Artificial Intelligence And Other Advanced Computing Stuff, Including How To Actually Use Python In These Fields Of Computing! Python is the primary programming language for advanced computing concepts ranging from machine learning, big data, data analytics, artificial intelligence and many others. What exactly do you need to learn? What's the place of python in big data, artificial intelligence, data science, machine learning, analytics etc.? If you have these and other related questions, this book is specially written for you, covering everything from basic to advanced stuff that will give you an above average understanding of using python for advanced computing. More precisely, the book covers: Why python is the most preferred programming language for advanced computing stuff like data analysis, big data, deep learning, machine learning, artificial intelligence and more How to handle object-oriented programming and why it is the best kind to handle data analysis. How all the advanced computing concepts like machine learning, deep learning, artificial intelligence and others relate and how python is at the center of it all How to handle different machine learning algorithms by leveraging the power of python to analyze any data you want Powerful tips and tricks that you can use to handle any problems in code, as they come Your Customers will never stop to use this book. Indeed; python is powerful, scalable, easy to use and much more, which are important ingredients for unleashing the full capabilities of advanced computing concepts like machine learning, deep learning, artificial intelligence, data science, data analytics and much more. Whether you want to learn python for advanced computing to give your business a competitive edge or want to learn python for advanced computing to add a new skill and possibly climb up the corporate ladder, this book has easy to follow steps to help you throughout the process. Buy it NOW If you Want To Make Your Customer Master in Python Programming Don't wait!
