Biznes IT
Nick McClure
TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow.This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.
Nick McClure
TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production.By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.
Ankit Jain, Dr. Amita Kapoor
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem.To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification.As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts.By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work.
Ankit Jain, Dr. Amita Kapoor
TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits—simplicity, efficiency, and flexibility—of using TensorFlow in various real-world projects. With the help of this book, you’ll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem.To start with, you’ll get to grips with using TensorFlow for machine learning projects; you’ll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification.As you make your way through the book, you’ll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You’ll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts.By the end of this book, you’ll have gained the required expertise to build full-fledged machine learning projects at work.
Md. Rezaul Karim
Predictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis.This book is a quick learning guide on all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will learn the linear regression model for regression analysis. You will also learn how to use regression for predicting continuous values. You will learn supervised learning algorithms for predictive analytics. You will explore unsupervised learning and clustering using K-meansYou will then learn how to predict neighborhoods using K-means, and then, see another example of clustering audio clips based on their audio features. This book is ideal for developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. This book is repurposed for this specific learning experience from material from Packt's Predictive Analytics with TensorFlow by Md. Rezaul Karim.
Md. Rezaul Karim
Predictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis.This book is a quick learning guide on all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will learn the linear regression model for regression analysis. You will also learn how to use regression for predicting continuous values. You will learn supervised learning algorithms for predictive analytics. You will explore unsupervised learning and clustering using K-meansYou will then learn how to predict neighborhoods using K-means, and then, see another example of clustering audio clips based on their audio features. This book is ideal for developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. This book is repurposed for this specific learning experience from material from Packt's Predictive Analytics with TensorFlow by Md. Rezaul Karim.
Kaushik Balakrishnan
Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving.The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator.By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems.
Kaushik Balakrishnan
Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving.The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator.By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems.
Mattias Fjellström
Terraform has revolutionized infrastructure as code, becoming an essential tool for IT professionals. With the Terraform Authoring and Operations Professional certification, you can validate your expertise and stand out in the competitive tech landscape. This guide not only deep dives into the core concepts of Terraform but also highlights practical examples, tips, and best practices to help you master the tool and secure your certification.This study guide covers all six exam objectives in detail, ensuring you are ready to tackle the exam with confidence. The book also covers practical tips to help you with the exam experience.This study guide assumes you have basic knowledge of Terraform workflows and the HCL language. Preferably, you are also familiar with network and compute resources on AWS. If you are willing to put in the extra work, even a novice Terraform and AWS user will benefit from this book.
Mattias Fjellström
Terraform has revolutionized infrastructure as code, becoming an essential tool for IT professionals. With the Terraform Authoring and Operations Professional certification, you can validate your expertise and stand out in the competitive tech landscape. This guide not only deep dives into the core concepts of Terraform but also highlights practical examples, tips, and best practices to help you master the tool and secure your certification.This study guide covers all six exam objectives in detail, ensuring you are ready to tackle the exam with confidence. The book also covers practical tips to help you with the exam experience.This study guide assumes you have basic knowledge of Terraform workflows and the HCL language. Preferably, you are also familiar with network and compute resources on AWS. If you are willing to put in the extra work, even a novice Terraform and AWS user will benefit from this book.
Justin Bozonier
Machine learning is the process of teaching machines to remember data patterns, using them to predict future outcomes, and offering choices that would appeal to individuals based on their past preferences.Machine learning is applicable to a lot of what you do every day. As a result, you can’t take forever to deliver your first iteration of software. Learning to build machine learning algorithms within a controlled test framework will speed up your time to deliver, quantify quality expectations with your clients, and enable rapid iteration and collaboration.This book will show you how to quantifiably test machine learning algorithms. The very different, foundational approach of this book starts every example algorithm with the simplest thing that could possibly work. With this approach, seasoned veterans will find simpler approaches to beginning a machine learning algorithm. You will learn how to iterate on these algorithms to enable rapid delivery and improve performance expectations.The book begins with an introduction to test driving machine learning and quantifying model quality. From there, you will test a neural network, predict values with regression, and build upon regression techniques with logistic regression. You will discover how to test different approaches to naïve bayes and compare them quantitatively, along with how to apply OOP (Object-Oriented Programming) and OOP patterns to test-driven code, leveraging SciKit-Learn.Finally, you will walk through the development of an algorithm which maximizes the expected value of profit for a marketing campaign by combining one of the classifiers covered with the multiple regression example in the book.
Testowanie pomysłów biznesowych. Biblioteka technik eksperymentacyjnych
David J. Bland, Alexander Osterwalder
Uważaj! Najpierw zgromadź dane, a dopiero potem wprowadzaj swój pomysł w życie. Choćby w teorii wydawał się najlepszy, najpierw rzetelnie go przetestuj! Praktyczny przewodnik - od pomysłu do sprawdzonej koncepcji biznesowej Specjalnie dla innowatorów z korporacji, założycieli start-upów i przedsiębiorców Odwołuje się do fundamentalnych modeli Customer Development oraz Lean Startup Zawiera niesamowitą, rozbudowaną bibliotekę technik szybkich eksperymentów Oceń trafność swojej koncepcji za pomocą mistrzowskiej metodologii! Spośród milionów śmiałych idei zaledwie niewielka część przynosi imponujący sukces, sławę i wielkie pieniądze. Pozostałe odchodzą w niepamięć. W bestsellerze Tworzenie modeli biznesowych opisano rewolucyjne narzędzia pracy dla wizjonerów. Książka zawiera techniki skutecznej weryfikacji trafności pomysłu na biznes i wyjaśnia cały proces testowania, począwszy od zaplanowania pierwszego eksperymentu. Dowiesz się z niej także, jak kształtować pożądane postawy zespołu: wypracujesz język i ceremoniał organizacji nastawionej na eksperyment. Najwyższy czas przestać ograniczać się do opinii i zdobyć niepodważalne dane! A zatem pojawił pomysł i jest szansa na sukces. Być może w przeszłości udało Ci się dokonać kilku niezłych wdrożeń. Teraz jednak chcesz wejść na wyższy poziom i nauczyć się testować pomysły, aby uniknąć oczywistych porażek. W tej książce znajdziesz najnowsze skuteczne rozwiązania praktyczne, oparte na sprawdzonych koncepcjach Steve'a Blanka: metodologiach Customer Development oraz "w teren!". Koniec z utartymi schematami i przestarzałymi rozwiązaniami! Skorzystaj z wiedzy i doświadczenia najsłynniejszych praktyków i strategów tej dziedziny, aby nauczyć się stosowania niezwykłych technik eksperymentów! Przed Tobą nowoczesny przewodnik po świecie szybkich testów, dzięki którym znajdziesz drogę do działalności na dużą skalę. Wybieraj spośród 44 praktycznych testów, z których każdy może przynieść Ci niemały dochód! Do dzieła! Przetestuj, zanim wdrożysz! Przystępnie podana praktyczna i potrzebna wiedza Liczne łatwe do zapamiętania rysunki i schematy Rozszerzające biznesową świadomość przykłady i komentarze
Testowanie pomysłów biznesowych. Biblioteka technik eksperymentacyjnych
David J. Bland, Alexander Osterwalder
Uważaj! Najpierw zgromadź dane, a dopiero potem wprowadzaj swój pomysł w życie. Choćby w teorii wydawał się najlepszy, najpierw rzetelnie go przetestuj! Praktyczny przewodnik - od pomysłu do sprawdzonej koncepcji biznesowej Specjalnie dla innowatorów z korporacji, założycieli start-upów i przedsiębiorców Odwołuje się do fundamentalnych modeli Customer Development oraz Lean Startup Zawiera niesamowitą, rozbudowaną bibliotekę technik szybkich eksperymentów Oceń trafność swojej koncepcji za pomocą mistrzowskiej metodologii! Spośród milionów śmiałych idei zaledwie niewielka część przynosi imponujący sukces, sławę i wielkie pieniądze. Pozostałe odchodzą w niepamięć. W bestsellerze Tworzenie modeli biznesowych opisano rewolucyjne narzędzia pracy dla wizjonerów. Książka zawiera techniki skutecznej weryfikacji trafności pomysłu na biznes i wyjaśnia cały proces testowania, począwszy od zaplanowania pierwszego eksperymentu. Dowiesz się z niej także, jak kształtować pożądane postawy zespołu: wypracujesz język i ceremoniał organizacji nastawionej na eksperyment. Najwyższy czas przestać ograniczać się do opinii i zdobyć niepodważalne dane! A zatem pojawił pomysł i jest szansa na sukces. Być może w przeszłości udało Ci się dokonać kilku niezłych wdrożeń. Teraz jednak chcesz wejść na wyższy poziom i nauczyć się testować pomysły, aby uniknąć oczywistych porażek. W tej książce znajdziesz najnowsze skuteczne rozwiązania praktyczne, oparte na sprawdzonych koncepcjach Steve'a Blanka: metodologiach Customer Development oraz "w teren!". Koniec z utartymi schematami i przestarzałymi rozwiązaniami! Skorzystaj z wiedzy i doświadczenia najsłynniejszych praktyków i strategów tej dziedziny, aby nauczyć się stosowania niezwykłych technik eksperymentów! Przed Tobą nowoczesny przewodnik po świecie szybkich testów, dzięki którym znajdziesz drogę do działalności na dużą skalę. Wybieraj spośród 44 praktycznych testów, z których każdy może przynieść Ci niemały dochód! Do dzieła! Przetestuj, zanim wdrożysz! Przystępnie podana praktyczna i potrzebna wiedza Liczne łatwe do zapamiętania rysunki i schematy Rozszerzające biznesową świadomość przykłady i komentarze