Serious Cryptography
This practical guide to modern encryption breaks down the fundamental mathematical concepts at the heart of cryptography without shying away from meaty discussions of how they work. You'll learn about authenticated encryption, secure randomness, hash functions, block ciphers, and public-key techniques such as RSA and elliptic curve cryptography. You'll also learn: Key concepts in cryptography, such as computational security, attacker models, and forward secrecy; The strengths and limitations of the TLS protocol behind HTTPS secure websites; Quantum computation and post-quantum cryptography; About various vulnerabilities by examining numerous code examples and use cases; How to choose the best algorithm or protocol and ask vendors the right questions. Each chapter includes a discussion of common implementation mistakes using real-world examples and details what could go wrong and how to avoid these pitfalls. Whether you're a seasoned practitioner or a beginner looking to dive i ...
This practical guide to modern encryption breaks down the fundamental mathematical concepts at the heart of cryptography without shying away from meaty discussions of how they work. You'll learn about authenticated encryption, secure randomness, hash functions, block ciphers, and public-key techniques such as RSA and elliptic curve cryptography. You'll also learn: Key concepts in cryptography, such as computational security, attacker models, and forward secrecy; The strengths and limitations of the TLS protocol behind HTTPS secure websites; Quantum computation and post-quantum cryptography; About various vulnerabilities by examining numerous code examples and use cases; How to choose the best algorithm or protocol and ask vendors the right questions. Each chapter includes a discussion of common implementation mistakes using real-world examples and details what could go wrong and how to avoid these pitfalls. Whether you're a seasoned practitioner or a beginner looking to dive i ...
Hands-On Machine Learning with Scikit-Learn and TensorFlow
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks - scikit-learn and TensorFlow - author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets; Use scikit-learn to track an example machine-learning project end-to-end; Explore several training models, including support vector machines, deci ...
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks - scikit-learn and TensorFlow - author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets; Use scikit-learn to track an example machine-learning project end-to-end; Explore several training models, including support vector machines, deci ...
Learning Bitcoin
Bitcoin exists as an open and transparent financial system without banks, governments, or corporate support. Simply put, Bitcoin is “programmable money” that has the potential to change the world on the same scale as the Internet itself. This book arms you with immense knowledge of Bitcoin and helps you implement the technology in your money matters, enabling secure transactions. We first walk through the fundamentals of Bitcoin, illustrate how the technology works, and exemplify how to interact with this powerful and new financial technology. You will learn how to set up your online Bitcoin wallet, indulge in buying and selling of bitcoins, and manage their storage. We then get to grips with the most powerful algorithm of all times: the Blockchain, and learn how crypto-currencies can reduce the risk of fraud for e-commerce merchants and consumers. ...
Bitcoin exists as an open and transparent financial system without banks, governments, or corporate support. Simply put, Bitcoin is “programmable money” that has the potential to change the world on the same scale as the Internet itself. This book arms you with immense knowledge of Bitcoin and helps you implement the technology in your money matters, enabling secure transactions. We first walk through the fundamentals of Bitcoin, illustrate how the technology works, and exemplify how to interact with this powerful and new financial technology. You will learn how to set up your online Bitcoin wallet, indulge in buying and selling of bitcoins, and manage their storage. We then get to grips with the most powerful algorithm of all times: the Blockchain, and learn how crypto-currencies can reduce the risk of fraud for e-commerce merchants and consumers. ...
Propeller Programming
Learn to program the propeller in Spin and C and how to map the Propeller Assembler language (PASM) from other high-level languages you might know. The overall task you will pursue in the book is to implement a Delta Compression algorithm: first in Spin, then in PASM, then in C. Along the way, you'll review Test Driven Development, a powerful technique for validating code, and conclude with a chapter on hardware manipulations. The book's main goal is to help you extend the capabilities of the Propeller processor by using the Assembler language. Use a data compression/decompression application to introduce PASM to the reader; Integrate C and PASM code; Review hardware interactions (setting and reading pins). ...
Learn to program the propeller in Spin and C and how to map the Propeller Assembler language (PASM) from other high-level languages you might know. The overall task you will pursue in the book is to implement a Delta Compression algorithm: first in Spin, then in PASM, then in C. Along the way, you'll review Test Driven Development, a powerful technique for validating code, and conclude with a chapter on hardware manipulations. The book's main goal is to help you extend the capabilities of the Propeller processor by using the Assembler language. Use a data compression/decompression application to introduce PASM to the reader; Integrate C and PASM code; Review hardware interactions (setting and reading pins). ...
D3.js in Action, 2nd Edition
Visualizing complex data is hard. Visualizing complex data on the web is darn near impossible without D3.js. D3 is a JavaScript library that provides a simple but powerful data visualization API over HTML, CSS, and SVG. Start with a structure, dataset, or algorithm; mix in D3; and you can programmatically generate static, animated, or interactive images that scale to any screen or browser. It's easy, and after a little practice, you'll be blown away by how beautiful your results can be! D3.js in Action, 2nd Edition is a completely updated revision of Manning's bestselling guide to data visualization with D3. You'll explore dozens of real-world examples in full-color, including force and network diagrams, workflow illustrations, geospatial constructions, and more! Along the way, you'll pick up best practices for building interactive graphics, animations, and live data representations. You'll also step through a fully interactive application created with D3 and React. ...
Visualizing complex data is hard. Visualizing complex data on the web is darn near impossible without D3.js. D3 is a JavaScript library that provides a simple but powerful data visualization API over HTML, CSS, and SVG. Start with a structure, dataset, or algorithm; mix in D3; and you can programmatically generate static, animated, or interactive images that scale to any screen or browser. It's easy, and after a little practice, you'll be blown away by how beautiful your results can be! D3.js in Action, 2nd Edition is a completely updated revision of Manning's bestselling guide to data visualization with D3. You'll explore dozens of real-world examples in full-color, including force and network diagrams, workflow illustrations, geospatial constructions, and more! Along the way, you'll pick up best practices for building interactive graphics, animations, and live data representations. You'll also step through a fully interactive application created with D3 and React. ...
Introduction to Deep Learning Business Applications for Developers
Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You'll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) ...
Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An Introduction to Deep Learning Business Applications for Developers covers some common DL algorithms such as content-based recommendation algorithms and natural language processing. You'll explore examples, such as video prediction with fully convolutional neural networks (FCNN) and residual neural networks (ResNets). You will also see applications of DL for controlling robotics, exploring the DeepQ learning algorithm with Monte Carlo Tree search (used to beat humans in the game of Go), and modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks (GANs) ...
Deep Learning with Applications Using Python
Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers intermediate and advanced levels of deep learning, including convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn; Build face recognition and face detection capabilit ...
Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such as chatbots, natural language processing, and face and object recognition. The goal is to equip you with the concepts, techniques, and algorithm implementations needed to create programs capable of performing deep learning. This book covers intermediate and advanced levels of deep learning, including convolutional neural networks, recurrent neural networks, and multilayer perceptrons. It also discusses popular APIs such as IBM Watson, Microsoft Azure, and scikit-learn. Work with various deep learning frameworks such as TensorFlow, Keras, and scikit-learn; Build face recognition and face detection capabilit ...
Machine Learning Solutions
Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You'll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you'll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, ...
Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You'll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you'll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, ...
Coding with Minecraft
You've mined for diamonds, crafted dozens of tools, and built all sorts of structures - but what if you could program robots to do all of that for you in a fraction of the time? In Coding with Minecraft, you'll create a virtual robot army with Lua, a programming language used by professional game developers. Step-by-step coding projects will show you how to write programs that automatically dig mines, collect materials, craft items, and build anything that you can imagine. Along the way, you'll explore key computer science concepts like data types, functions, variables, and more. Program robots that make smart decisions with flow control; Reuse code so that your robots can farm any crop you want, including wheat, sugar cane, and even cacti; Program a factory that generates infinite building supplies; Design an algorithm for creating walls and buildings of any size; Code yourself a pickaxe-swinging robotic lumberjack; Create a robot that digs mine shafts with stairs so you can exp ...
You've mined for diamonds, crafted dozens of tools, and built all sorts of structures - but what if you could program robots to do all of that for you in a fraction of the time? In Coding with Minecraft, you'll create a virtual robot army with Lua, a programming language used by professional game developers. Step-by-step coding projects will show you how to write programs that automatically dig mines, collect materials, craft items, and build anything that you can imagine. Along the way, you'll explore key computer science concepts like data types, functions, variables, and more. Program robots that make smart decisions with flow control; Reuse code so that your robots can farm any crop you want, including wheat, sugar cane, and even cacti; Program a factory that generates infinite building supplies; Design an algorithm for creating walls and buildings of any size; Code yourself a pickaxe-swinging robotic lumberjack; Create a robot that digs mine shafts with stairs so you can exp ...
Mastering Machine Learning Algorithms
Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by maki ...
Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour. Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by maki ...