Practical AI on the Google Cloud Platform
Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application. Learn key concepts for data science, machine learning, and deep learning; Explore tools like Video AI and AutoML Tables; Build a simple language processor using deep learning systems; Perform image recognition using CNNs, transfer learning, and GANs; U ...
Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. Author Micheal Lanham demonstrates methods for building and training models step-by-step and shows you how to expand your models to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, you'll quickly get up to speed with Google Cloud Platform, whether you want to build an AI assistant or a simple business AI application. Learn key concepts for data science, machine learning, and deep learning; Explore tools like Video AI and AutoML Tables; Build a simple language processor using deep learning systems; Perform image recognition using CNNs, transfer learning, and GANs; U ...
Learn Programming
This book is aimed at readers who are interested in software development but have very little to no prior experience. The book focuses on teaching the core principles around software development. It uses several technologies to this goal (e.g. C, Python, JavaScript, HTML, etc.) but is not a book about the technologies themselves. The reader will learn the basics (or in some cases more) of various technologies along the way, but the focus is on building a foundation for software development. The book is your guided tour through the programming jungle, aiming to provide some clarity and build the foundation for software development skills. ...
This book is aimed at readers who are interested in software development but have very little to no prior experience. The book focuses on teaching the core principles around software development. It uses several technologies to this goal (e.g. C, Python, JavaScript, HTML, etc.) but is not a book about the technologies themselves. The reader will learn the basics (or in some cases more) of various technologies along the way, but the focus is on building a foundation for software development. The book is your guided tour through the programming jungle, aiming to provide some clarity and build the foundation for software development skills. ...
Machine Learning for Algorithmic Trading, 2nd Edition
The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This thoroughly revised and expanded 2nd edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This edition introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this workflow using examples that range from linear models and tree-based ensembles to deep-learning techniques from the cutting edge of the research frontier. This revised version shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable a machine learning model to predict returns f ...
The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This thoroughly revised and expanded 2nd edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This edition introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this workflow using examples that range from linear models and tree-based ensembles to deep-learning techniques from the cutting edge of the research frontier. This revised version shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable a machine learning model to predict returns f ...
Software Engineering for Absolute Beginners
Start programming from scratch, no experience required. This beginners' guide to software engineering starts with a discussion of the different editors used to create software and covers setting up a Docker environment. Next, you will learn about repositories and version control along with its uses. Now that you are ready to program, you'll go through the basics of Python, the ideal language to learn as a novice software engineer. Many modern applications need to talk to a database of some kind, so you will explore how to create and connect to a database and how to design one for your app. Additionally you will discover how to use Python's Flask microframework and how to efficiently test your code. Finally, the book explains best practices in coding, design, deployment, and security. Software Engineering for Absolute Beginners answers the question of what topics you should know when you start out to learn software engineering. This book covers a lot of topics, and aims to clarify t ...
Start programming from scratch, no experience required. This beginners' guide to software engineering starts with a discussion of the different editors used to create software and covers setting up a Docker environment. Next, you will learn about repositories and version control along with its uses. Now that you are ready to program, you'll go through the basics of Python, the ideal language to learn as a novice software engineer. Many modern applications need to talk to a database of some kind, so you will explore how to create and connect to a database and how to design one for your app. Additionally you will discover how to use Python's Flask microframework and how to efficiently test your code. Finally, the book explains best practices in coding, design, deployment, and security. Software Engineering for Absolute Beginners answers the question of what topics you should know when you start out to learn software engineering. This book covers a lot of topics, and aims to clarify t ...
TensorFlow 2.x in the Colaboratory Cloud
Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow 2.x along with Colab's easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything else - Python, TensorFlow 2.x, GPU support, and Jupyter Notebooks - is provided and ready to go from Colab. The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and testing. You will fi ...
Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab's default install of the most current TensorFlow 2.x along with Colab's easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything else - Python, TensorFlow 2.x, GPU support, and Jupyter Notebooks - is provided and ready to go from Colab. The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and testing. You will fi ...
A Common-Sense Guide to Data Structures and Algorithms, 2nd Edition
If you thought that data structures and algorithms were all just theory, you're missing out on what they can do for your code. Learn to use Big O Notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. This new edition features practice exercises in every chapter, and new chapters on topics such as dynamic programming and heaps and tries. Get the hands-on info you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that ...
If you thought that data structures and algorithms were all just theory, you're missing out on what they can do for your code. Learn to use Big O Notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. This new edition features practice exercises in every chapter, and new chapters on topics such as dynamic programming and heaps and tries. Get the hands-on info you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that ...
Data Pipelines with Apache Airflow
A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, keeping every process along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. Its easy-to-use UI, plug-and-play options, and flexible Python scripting make Airflow perfect for any data management task. Data Pipelines with Apache Airflow teaches you how to build an ...
A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, keeping every process along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, Data Pipelines with Apache Airflow teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack. Data pipelines manage the flow of data from initial collection through consolidation, cleaning, analysis, visualization, and more. Apache Airflow provides a single platform you can use to design, implement, monitor, and maintain your pipelines. Its easy-to-use UI, plug-and-play options, and flexible Python scripting make Airflow perfect for any data management task. Data Pipelines with Apache Airflow teaches you how to build an ...
Automated Machine Learning with Microsoft Azure
Automated Machine Learning with Microsoft Azure helps you to build high-performing, accurate machine learning models in record time. It allows anyone to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. With a series of clicks on a guided user interface (GUI), novices and seasoned data scientists alike can train and deploy machine learning solutions to production with ease. This book will teach you how to use Azure AutoML with both the GUI as well as the AzureML Python software development kit (SDK) in a careful, step-by-step way. First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train ...
Automated Machine Learning with Microsoft Azure helps you to build high-performing, accurate machine learning models in record time. It allows anyone to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. With a series of clicks on a guided user interface (GUI), novices and seasoned data scientists alike can train and deploy machine learning solutions to production with ease. This book will teach you how to use Azure AutoML with both the GUI as well as the AzureML Python software development kit (SDK) in a careful, step-by-step way. First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train ...
Classical Object-Oriented Programming with ECMAScript
ECMAScript (more popularly known by the name "JavaScript") is the language of the web. In the decades past, it has been used to augment web pages with trivial features and obnoxious gimmicks. Today, the language is used to write full-featured web applications that rival modern desktop software in nearly every regard and has even expanded to create desktop and server software. With increased usage, there is a desire to apply more familiar development paradigms while continuing to take advantage of the language's incredibly flexible functional and prototypal models. Of all of the modern paradigms, one of the most influential and widely adopted is the Classical Object-Oriented paradigm, as represented in languages such as Java, C++, Python, Perl, PHP and others. ECMAScript, as an object-oriented language, contains many features familiar to Classical OO developers. However, certain features remain elusive. This paper will detail the development of a classical object-oriented framework f ...
ECMAScript (more popularly known by the name "JavaScript") is the language of the web. In the decades past, it has been used to augment web pages with trivial features and obnoxious gimmicks. Today, the language is used to write full-featured web applications that rival modern desktop software in nearly every regard and has even expanded to create desktop and server software. With increased usage, there is a desire to apply more familiar development paradigms while continuing to take advantage of the language's incredibly flexible functional and prototypal models. Of all of the modern paradigms, one of the most influential and widely adopted is the Classical Object-Oriented paradigm, as represented in languages such as Java, C++, Python, Perl, PHP and others. ECMAScript, as an object-oriented language, contains many features familiar to Classical OO developers. However, certain features remain elusive. This paper will detail the development of a classical object-oriented framework f ...
Deep Reinforcement Learning in Unity
Gain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity. This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn about: deep learning and work through an introduction to Tensorflow for writing neural networks (including perceptron, convolution, and LSTM networks), Q learning with Unity ML agents, and porting trained neural network models in Unity through the Python-C# API. You will also explore the OpenAI Gym Environment used throughout the book. Deep Reinforcement ...
Gain an in-depth overview of reinforcement learning for autonomous agents in game development with Unity. This book starts with an introduction to state-based reinforcement learning algorithms involving Markov models, Bellman equations, and writing custom C# code with the aim of contrasting value and policy-based functions in reinforcement learning. Then, you will move on to path finding and navigation meshes in Unity, setting up the ML Agents Toolkit (including how to install and set up ML agents from the GitHub repository), and installing fundamental machine learning libraries and frameworks (such as Tensorflow). You will learn about: deep learning and work through an introduction to Tensorflow for writing neural networks (including perceptron, convolution, and LSTM networks), Q learning with Unity ML agents, and porting trained neural network models in Unity through the Python-C# API. You will also explore the OpenAI Gym Environment used throughout the book. Deep Reinforcement ...