Daily Dose for 2017.10.17

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Mastering Metasploit - Second Edition
JavaScript Recipes
Keras in Motion
Deep Learning with Python
Grokking Deep Learning


Books/Videos on Sale (or Free) Today

These deals are good for today only, so be sure to take advantage of the pricing before the offers expire.

Free Mastering Metasploit - Second Edition

Mastering Metasploit - Second Edition Free Packt eBook by Nipun Jaswal (valid through 10/17 at 19:00 EST). This book covers Metasploit, Penetration Testing, Railgun, SCADA, ICS, VOIP, Armitage, Cortana.

Publisher’s Description

Metasploit is a popular penetration testing framework that has one of the largest exploit databases around. This book will show you exactly how to prepare yourself against the attacks you will face every day by simulating real-world possibilities.

We start by reminding you about the basic functionalities of Metasploit and its use in the most traditional ways. You’ll get to know about the basics of programming Metasploit modules as a refresher, and then dive into carrying out exploitation as well building and porting exploits of various kinds in Metasploit.

In the next section, you’ll develop the ability to perform testing on various services such as SCADA, databases, IoT, mobile, tablets, and many more services. After this training, we jump into real-world sophisticated scenarios where performing penetration tests are a challenge. With real-life case studies, we take you on a journey through client-side attacks using Metasploit and various scripts built on the Metasploit framework.

By the end of the book, you will be trained specifically on time-saving techniques using Metasploit.

What You Will Learn

  • Develop advanced and sophisticated auxiliary modules
  • Port exploits from PERL, Python, and many more programming languages
  • Test services such as databases, SCADA, and many more
  • Attack the client side with highly advanced techniques
  • Test mobile and tablet devices with Metasploit
  • Perform social engineering with Metasploit
  • Simulate attacks on web servers and systems with Armitage GUI
  • Script attacks in Armitage using CORTANA scripting

About the Author

Nipun Jaswal is an IT security business executive and a passionate IT security researcher with more than seven years of professional experience, who possesses knowledge in all aspects of IT security testing and implementation, with expertise in managing cross-cultural teams and planning the execution of security needs beyond national boundaries.

He is an M.tech in Computer Sciences and a thought leader who has contributed to raising the bar of understanding on cyber safety and ethical hacking among students of many colleges and universities in India. He is a voracious public speaker and talks about improving IT security, insider threats, social engineering, wireless forensics, and exploit writing. He is the author of numerous IT security articles with modern security magazines such as Eforensics, Hakin9, Security Kaizen, and many more. Many famous companies, such as Apple, Microsoft, AT&T, Offensive Security, Rapid7, Blackberry, Nokia, www.zynga.com, and many others have thanked him for finding vulnerabilities in their systems. He has also been acknowledged with the Award of Excellence from the National Cyber Defense and Research Center (NCDRC) for his tremendous contributions to the IT security industry.

In his current profile, he leads a team of super specialists in cyber security to protect various clients from cyber security threats and network intrusion by providing permanent solutions and services. Please feel free to contact him via e-mail at mail@nipunjaswal.info.

$9.99 JavaScript Recipes

JavaScript Recipes $9.99 Apress eBook by Russ Ferguson, Keith Cirkel. This book covers JavaScript, Node.js, jQuery.

Publisher’s Description

  • Right up-to-date with the latest version of JavaScript
  • Includes recipes for using frameworks and Node.js as well as the main JavaScript recipes
  • Shows how applications can function more efficiently and features different aspects of frameworks such as jQuery

Quickly discover solutions to common problems, best practices you can follow, and everything JavaScript has to offer. Using a problem-solution approach, this book takes you from language basics like built-in objects and flow control all the way to advanced optimization techniques, frameworks and Node.js.

With JavaScript Recipes you will learn language fundamentals like types, conversions, execution contexts, expressions, operators, statements, and built-in objects. You’ll explore and make the most of your script’s host environment and how to create your own JavaScript host using Google’s V8 engine. Employ advanced optimization techniques to create scripts that execute as fast, or faster, than native executables.

JavaScript Recipes shows you how to avoid wasting development time and concentrate on developing cutting-edge applications. You’ll see how much quicker and efficient it is to develop with JavaScript. Start becoming a JavaScript pro with JavaScript Recipes today.

What You’ll Learn

  • Learn JavaScript language fundamentals and what they can do for you
  • Use JavaScript’s powerful features to develop next-generation applications
  • Explore your script’s host environment and extend it with your own objects
  • Learn how to use Google’s V8 Engine to create your own JavaScript environment
  • Learn advanced optimization techniques
  • Implement advanced techniques like closures, namespaces, and reflection
  • How to use Node.js efficiently

Who This Book Is For

JavaScript developers who need to get development tasks accomplished quickly.

About the Authors

Russ Ferguson is a freelance developer and instructor in the New York City area. His interest in computers goes back to Atari Basic, CompuServe and BBS systems in the mid-1980s. For over 10 years, he has been fortunate to teach at Pratt Institute, where subjects have been as diverse as the student body. Working in New York has given him the opportunity to work with a diverse group of companies whose projects ranged from developing real-time chat/video applications for start-ups to developing and managing content management systems for established Media and Advertising agencies like MTV and DC Comics.

Keith Cirkel is a JavaScript Consultant from London, United Kingdom, specializing in writing open source JavaScript libraries and literature. To find out more about his work, visit https://www.keithcirkel.co.uk/, reach him via GitHub at github.com/keithamus, or Twitter at twitter.com/keithamus.

50% off Keras in Motion

Keras in Motion 50% off Manning’s eBook by Dan Van Boxel. This book covers Keras, Python, Deep Learning, Neural Networks, Machine Learning, Tensorflow, Theano, Autoencoders.

Publisher’s Description

See it. Do it. Learn it! Keras in Motion introduces you to the amazing Keras deep learning library through high-quality video-based lessons and built-in exercises, so you can put what you learn into practice.

Keras in Motion teaches you to build neural-network models for real-world data problems using Python and Keras. In over two hours of hands-on, practical video lessons, you’ll apply Keras to common machine learning scenarios, ranging from regression and classification to implementing Autoencoders and applying transfer learning. In each crystal-clear video module, you’ll put your new knowledge into practice, as you teach your network to recognize text and even create an algorithm for a self-driving car!

About the subject

Keras is a Python library designed to take the stress out of deep learning. The Keras library provides a library of high-level building blocks on top of the low-level features of the TensorFlow and Theano machine learning frameworks. In Keras, you define deep learning models without specifying the detailed mathematics and other mechanics, so you can focus on what you want to accomplish. Built with experimentation and prototyping in mind, Keras has a super friendly API and an intuitive Python-based coding style. With over 50,000 users, Keras is the perfect choice for any developer working with data.


Written for intermediate-level data scientists, developers, and machine learning engineers. Code examples are in Python.

What you will learn

  • Regression and classification problems
  • Using neural networks for image processing
  • Building autoencoders
  • Designing and implementing a self-driving car
  • Hands-on coding with practical exercises and example

About the instructor

Dan Van Boxel is an engineer and data scientist with a background in both engineering and mathematics. On his livestream, Dan demonstrates a different machine learning library, method, or model weekly.

50% off Deep Learning with Python

Deep Learning with Python 50% off Manning’s eBook by Francois Chollet. This book covers Keras, Deep Learning, Python, Neural Networks, Machine Learning, Artificial Intelligence.

Publisher’s Description

Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.

In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here’s a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, “dog,” “cat,” etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

About the technology

Keras is one of the most widely used deep learning frameworks for Python. Keras puts ease of use and accessibility front and center, making it a great fit for getting started with deep learning. Besides being easy to work with, it is suitable for the most advanced use cases as well: almost all deep learning competitions on Kaggle.com are won using Keras code.

About the book

Deep Learning with Python is for developers with some Python experience who want to learn how to use deep learning to solve real-world problems. The book is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. You begin by finding out what deep learning is, and how it connects with Artificial Intelligence and Machine Learning, as well as why deep learning is rapidly gaining in importance right now. You will then learn the fundamentals of machine learning, and finally, you will dive deeper into practical applications in computer vision, natural language processing, and more. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects.

What’s inside

  • Understanding key machine learning concepts
  • Setting up a computer environment for deep learning
  • Using convolutional neural networks to solve image classification tasks
  • Understanding and visualizing the representations that neural networks learn
  • Using recurrent neural networks to solve text and sequence classification tasks
  • Using deep learning for image style transfer, text generation and image generation
  • Written by the creator of Keras, the Python deep learning library

About the reader

Readers should have Python experience. No previous experience with machine learning or deep learning is required.

About the author

Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural networks since 2012. Francois is currently doing deep learning research at Google. He blogs about deep learning at blog.keras.io.

50% off Grokking Deep Learning

Grokking Deep Learning 50% off Manning’s eBook by Andrew W. Trask. This book covers Deep Learning, Artificial Intelligence, Neural Networks, Machine Learning, Python, Gradient Descent, MNIST, Natural Language Processing.

Publisher’s Description

Artificial Intelligence is one of the most exciting technologies of the century, and Deep Learning is in many ways the “brain” behind some of the world’s smartest Artificial Intelligence systems out there. Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the intelligence of their human creators, defeating the world champion Go player, achieving superhuman performance on video games, driving cars, translating languages, and sometimes even helping law enforcement fight crime. Deep Learning is a revolution that is changing every industry across the globe.

Grokking Deep Learning is the perfect place to begin your deep learning journey. Rather than just learn the “black box” API of some library or framework, you will actually understand how to build these algorithms completely from scratch. You will understand how Deep Learning is able to learn at levels greater than humans. You will be able to understand the “brain” behind state-of-the-art Artificial Intelligence. Furthermore, unlike other courses that assume advanced knowledge of Calculus and leverage complex mathematical notation, if you’re a Python hacker who passed high-school algebra, you’re ready to go. And at the end, you’ll even build an A.I. that will learn to defeat you in a classic Atari game.

About the technology

Artificial Intelligence is one of the most exciting technologies of the century, and Deep Learning is in many ways the “brain” behind some of the world’s smartest Artificial Intelligence systems out there.

What’s inside

  • How neural networks “learn”
  • You will build neural networks that can see and understand images
  • You will build neural networks that can translate text between languages and even write like Shakespeare
  • You will build neural networks that can learn how to play videogames

About the reader

Written for readers with high school-level math and intermediate programming skills. Experience with Calculus is helpful but NOT required.

About the author

Andrew Trask is a PhD student at Oxford University, funded by the Oxford-DeepMind Graduate Scholarship, where he researches Deep Learning approaches with special emphasis on human language. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning where he trained the world’s largest artificial neural network with over 160 billion parameters, and helped guide the analytics roadmap for the Synthesys cognitive computing platform which tackles some of the most complex analysis tasks across government intelligence, finance, and healthcare industries.

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