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Pandas 1x Cookbook
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Book Synopsis The Kung Fu Panda Cookbook by : Sharon Powell
Download or read book The Kung Fu Panda Cookbook written by Sharon Powell and published by . This book was released on 2020-11-02 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you actually ready to dive into the world of Kung Fu Panda? Kung Fu Panda, an animated movie series, is one of the most famous and loved series in the world. It is not only famous among kids but among all generations alike. The cuteness of a panda with the combination of Kung Fu is delightful to watch. All the characters in the movie are well placed and described. So, here is a cookbook solely dedicated to the amazing animated series. We are sure all the dishes that were shown in the movie made you jealous - be it the noodle soup, the peaches, or even the bean buns that Po had created a record for. Everything looked very delicious and tasty, and all we wanted to do was to grab the dishes and enjoy them. All the recipes in this cookbook are crafted keeping in mind all the factors, characters, scenes, and culture from the movie. For all the recipes mentioned, you don't have to have the skills of Gordon Ramsay. Just some creativity, a few easily available ingredients, and this cookbook are all you need. So, head over to your kitchen and create the wonderful dishes for your family and friends.
Book Synopsis TensorFlow 1.x Deep Learning Cookbook by : Antonio Gulli
Download or read book TensorFlow 1.x Deep Learning Cookbook written by Antonio Gulli and published by Packt Publishing Ltd. This book was released on 2017-12-12 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x About This Book Skill up and implement tricky neural networks using Google's TensorFlow 1.x An easy-to-follow guide that lets you explore reinforcement learning, GANs, autoencoders, multilayer perceptrons and more. Hands-on recipes to work with Tensorflow on desktop, mobile, and cloud environment Who This Book Is For This book is intended for data analysts, data scientists, machine learning practitioners and deep learning enthusiasts who want to perform deep learning tasks on a regular basis and are looking for a handy guide they can refer to. People who are slightly familiar with neural networks, and now want to gain expertise in working with different types of neural networks and datasets, will find this book quite useful. What You Will Learn Install TensorFlow and use it for CPU and GPU operations Implement DNNs and apply them to solve different AI-driven problems. Leverage different data sets such as MNIST, CIFAR-10, and Youtube8m with TensorFlow and learn how to access and use them in your code. Use TensorBoard to understand neural network architectures, optimize the learning process, and peek inside the neural network black box. Use different regression techniques for prediction and classification problems Build single and multilayer perceptrons in TensorFlow Implement CNN and RNN in TensorFlow, and use it to solve real-world use cases. Learn how restricted Boltzmann Machines can be used to recommend movies. Understand the implementation of Autoencoders and deep belief networks, and use them for emotion detection. Master the different reinforcement learning methods to implement game playing agents. GANs and their implementation using TensorFlow. In Detail Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial intelligence. This exciting recipe-based guide will take you from the realm of DNN theory to implementing them practically to solve the real-life problems in artificial intelligence domain. In this book, you will learn how to efficiently use TensorFlow, Google's open source framework for deep learning. You will implement different deep learning networks such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Deep Q-learning Networks (DQNs), and Generative Adversarial Networks (GANs) with easy to follow independent recipes. You will learn how to make Keras as backend with TensorFlow. With a problem-solution approach, you will understand how to implement different deep neural architectures to carry out complex tasks at work. You will learn the performance of different DNNs on some popularly used data sets such as MNIST, CIFAR-10, Youtube8m, and more. You will not only learn about the different mobile and embedded platforms supported by TensorFlow but also how to set up cloud platforms for deep learning applications. Get a sneak peek of TPU architecture and how they will affect DNN future. By using crisp, no-nonsense recipes, you will become an expert in implementing deep learning techniques in growing real-world applications and research areas such as reinforcement learning, GANs, autoencoders and more. Style and approach This book consists of hands-on recipes where you'll deal with real-world problems. You'll execute a series of tasks as you walk through data mining challenges using TensorFlow 1.x. Your one-stop solution for common and not-so-common pain points, this is a book that you must have on the shelf.
Book Synopsis Pandas Cookbook by : Theodore Petrou
Download or read book Pandas Cookbook written by Theodore Petrou and published by Packt Publishing Ltd. This book was released on 2017-10-23 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysis About This Book Use the power of pandas to solve most complex scientific computing problems with ease Leverage fast, robust data structures in pandas to gain useful insights from your data Practical, easy to implement recipes for quick solutions to common problems in data using pandas Who This Book Is For This book is for data scientists, analysts and Python developers who wish to explore data analysis and scientific computing in a practical, hands-on manner. The recipes included in this book are suitable for both novice and advanced users, and contain helpful tips, tricks and caveats wherever necessary. Some understanding of pandas will be helpful, but not mandatory. What You Will Learn Master the fundamentals of pandas to quickly begin exploring any dataset Isolate any subset of data by properly selecting and querying the data Split data into independent groups before applying aggregations and transformations to each group Restructure data into tidy form to make data analysis and visualization easier Prepare real-world messy datasets for machine learning Combine and merge data from different sources through pandas SQL-like operations Utilize pandas unparalleled time series functionality Create beautiful and insightful visualizations through pandas direct hooks to Matplotlib and Seaborn In Detail This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced recipes combine several different features across the pandas library to generate results. Style and approach The author relies on his vast experience teaching pandas in a professional setting to deliver very detailed explanations for each line of code in all of the recipes. All code and dataset explanations exist in Jupyter Notebooks, an excellent interface for exploring data.
Download or read book Hello, Cupcake! written by Karen Tack and published by Houghton Mifflin Harcourt. This book was released on 2009-07-31 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: New York Times Bestseller: Sweeten special occasions with these easy recipes for creative cupcakes using common candies. With hundreds of brilliant photos, this cookbook features witty, one-of-a-kind, imaginative cupcake designs using candies from the local convenience store, no baking skills or fancy pastry equipment required. Create funny, scary, and sophisticated masterpieces using a ziplock bag and common candies and snack items. With these easy-to-follow techniques, even the most kitchen-challenged cooks can: • raise a big-top circus cupcake tier for a kid's birthday • plant candy vegetables on Oreo earth cupcakes for a garden party • trot out a line of confectionery “pup cakes” for a dog fancier • serve spaghetti and meatball cupcakes for April Fool's Day • bewitch trick-or-treaters with eerie alien cupcakes • create holidays on icing with a white Christmas cupcake wreath, turkey cupcake place cards, and Easter egg cupcakes
Book Synopsis Pandas Love Pickles: Let's Eat! by :
Download or read book Pandas Love Pickles: Let's Eat! written by and published by . This book was released on 2021-11-20 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Pandas Love Pickles: Let's Eat encourages your kids to explore new foods with ABC recipes and crafts inspired by the Pandas Love series! With colorful recipes and simple food art, this book can make even the most reluctant eater interested in mealtime. These recipes and crafts are fun to make, eat and explore.
Download or read book Pandas written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Foolproof Preserving and Canning by : America's Test Kitchen
Download or read book Foolproof Preserving and Canning written by America's Test Kitchen and published by America's Test Kitchen. This book was released on 2016-04-26 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every home cook's essential step-by-step guide to canning and preserving 100 can't-fail sweet and savory recipes, from tried-and-true classics to modern updates. The experts at America's Test Kitchen show you how to easily (and safely) make homemade everything—from fruity jams with beautiful summer berries to piquant pickles from raw vegetables of all kinds—with detailed tutorials, troubleshooting tips, equipment information, instruction on doubling batches, and insight into the science behind canning (How much salt should you use? What's the perfect preserving temperature?). No matter what season it is, which jars you have, or how much time you have, this book has something for everyone, beginner or expert. Sweet Jams & Jellies: Once you’ve turned out flawless favorites like Raspberry & Strawberry, try your hand at Blueberry Earl Grey Jam. Savory Jams & Chutneys: Start with classics like Caramelized Onion Jam and then make a delicious Apple Shallot Chutney to pair with a favorite dish. Vegetable Pickles: Simply cooked in a vinegar brine or long-fermented, every pickle is perfectly crisp. Fruit in Syrup: Enjoy jewel-like fruit, from bite-size to whole, in a syrup made of the perfect ratio of water to sugar. Tomatoes: Intensify their flavor through roasting or lock in summer sweetness with fresh tomato sauce. Canning Books Are Hot More and more people are canning and preserving at home for the satisfaction of tranforming raw height-of-season produce into jewel-like jars of jams, jellies, and condiments, or umami-packed pickles. Step-by-Step Instruction This is the first canning and preserving book from ATK; we take the mystery and fear away and provide detailed and illustrated instructions for every recipe. Timelines for Every Recipe It's helpful to have snapshot of the commitment involved in making the recipe—and when they're ready to eat. Lots of Options for Both Beginner and Experienced Canners There is a lot of interest in handcrafting small batches of fruits and vegetables. The emphasis in this book is on small batch canning (2- or 4-jar yields) with double-it options for all the 4 jar recipes. Beautiful Package Completely illustrated with step photos of the recipes in progress and an easy-to follow design.
Book Synopsis Cleaning Data for Effective Data Science by : David Mertz
Download or read book Cleaning Data for Effective Data Science written by David Mertz and published by Packt Publishing Ltd. This book was released on 2021-03-31 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: Think about your data intelligently and ask the right questions Key FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of each chapterBook Description Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way. In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with. Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for academic courses. What you will learnIngest and work with common data formats like JSON, CSV, SQL and NoSQL databases, PDF, and binary serialized data structuresUnderstand how and why we use tools such as pandas, SciPy, scikit-learn, Tidyverse, and BashApply useful rules and heuristics for assessing data quality and detecting bias, like Benford’s law and the 68-95-99.7 ruleIdentify and handle unreliable data and outliers, examining z-score and other statistical propertiesImpute sensible values into missing data and use sampling to fix imbalancesUse dimensionality reduction, quantization, one-hot encoding, and other feature engineering techniques to draw out patterns in your dataWork carefully with time series data, performing de-trending and interpolationWho this book is for This book is designed to benefit software developers, data scientists, aspiring data scientists, teachers, and students who work with data. If you want to improve your rigor in data hygiene or are looking for a refresher, this book is for you. Basic familiarity with statistics, general concepts in machine learning, knowledge of a programming language (Python or R), and some exposure to data science are helpful.
Download or read book Guide to NumPy written by Travis Oliphant and published by CreateSpace. This book was released on 2015-09-15 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second edition of Travis Oliphant's A Guide to NumPy originally published electronically in 2006. It is designed to be a reference that can be used by practitioners who are familiar with Python but want to learn more about NumPy and related tools. In this updated edition, new perspectives are shared as well as descriptions of new distributed processing tools in the ecosystem, and how Numba can be used to compile code using NumPy arrays. Travis Oliphant is the co-founder and CEO of Continuum Analytics. Continuum Analytics develops Anaconda, the leading modern open source analytics platform powered by Python. Travis, who is a passionate advocate of open source technology, has a Ph.D. from Mayo Clinic and B.S. and M.S. degrees in Mathematics and Electrical Engineering from Brigham Young University. Since 1997, he has worked extensively with Python for computational and data science. He was the primary creator of the NumPy package and founding contributor to the SciPy package. He was also a co-founder and past board member of NumFOCUS, a non-profit for reproducible and accessible science that supports the PyData stack. He also served on the board of the Python Software Foundation.
Book Synopsis Eat to Beat Disease by : William W Li
Download or read book Eat to Beat Disease written by William W Li and published by Balance. This book was released on 2019-03-19 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eat your way to better health with this New York Times bestseller on food's ability to help the body heal itself from cancer, dementia, and dozens of other avoidable diseases. Forget everything you think you know about your body and food, and discover the new science of how the body heals itself. Learn how to identify the strategies and dosages for using food to transform your resilience and health in Eat to Beat Disease. We have radically underestimated our body's power to transform and restore our health. Pioneering physician scientist, Dr. William Li, empowers readers by showing them the evidence behind over 200 health-boosting foods that can starve cancer, reduce your risk of dementia, and beat dozens of avoidable diseases. Eat to Beat Disease isn't about what foods to avoid, but rather is a life-changing guide to the hundreds of healing foods to add to your meals that support the body's defense systems, including: Plums Cinnamon Jasmine tea Red wine and beer Black Beans San Marzano tomatoes Olive oil Pacific oysters Cheeses like Jarlsberg, Camembert and cheddar Sourdough bread The book's plan shows you how to integrate the foods you already love into any diet or health plan to activate your body's health defense systems-Angiogenesis, Regeneration, Microbiome, DNA Protection, and Immunity-to fight cancer, diabetes, cardiovascular, neurodegenerative autoimmune diseases, and other debilitating conditions. Both informative and practical, Eat to Beat Disease explains the science of healing and prevention, the strategies for using food to actively transform health, and points the science of wellbeing and disease prevention in an exhilarating new direction.
Book Synopsis TensorFlow Deep Learning Projects by : Alexey Grigorev
Download or read book TensorFlow Deep Learning Projects written by Alexey Grigorev and published by Packt Publishing Ltd. This book was released on 2018-03-28 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios Key Features Build efficient deep learning pipelines using the popular Tensorflow framework Train neural networks such as ConvNets, generative models, and LSTMs Includes projects related to Computer Vision, stock prediction, chatbots and more Book Description TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects. TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. Learn to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing so, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation, and use reinforcement learning techniques to play games. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently. What you will learn Set up the TensorFlow environment for deep learning Construct your own ConvNets for effective image processing Use LSTMs for image caption generation Forecast stock prediction accurately with an LSTM architecture Learn what semantic matching is by detecting duplicate Quora questions Set up an AWS instance with TensorFlow to train GANs Train and set up a chatbot to understand and interpret human input Build an AI capable of playing a video game by itself –and win it! Who this book is for This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.
Download or read book Effective Python written by Brett Slatkin and published by Pearson Education. This book was released on 2015 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Effective Python will help students harness the full power of Python to write exceptionally robust, efficient, maintainable, and well-performing code. Utilizing the concise, scenario-driven style pioneered in Scott Meyers's best-selling Effective C++, Brett Slatkin brings together 53 Python best practices, tips, shortcuts, and realistic code examples from expert programmers. Each section contains specific, actionable guidelines organized into items, each with carefully worded advice supported by detailed technical arguments and illuminating examples.
Book Synopsis Dive Into Deep Learning by : Joanne Quinn
Download or read book Dive Into Deep Learning written by Joanne Quinn and published by Corwin Press. This book was released on 2019-07-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself.
Download or read book Edible Insects written by Arnold van Huis and published by Bright Sparks. This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edible insects have always been a part of human diets, but in some societies there remains a degree of disdain and disgust for their consumption. Although the majority of consumed insects are gathered in forest habitats, mass-rearing systems are being developed in many countries. Insects offer a significant opportunity to merge traditional knowledge and modern science to improve human food security worldwide. This publication describes the contribution of insects to food security and examines future prospects for raising insects at a commercial scale to improve food and feed production, diversify diets, and support livelihoods in both developing and developed countries. It shows the many traditional and potential new uses of insects for direct human consumption and the opportunities for and constraints to farming them for food and feed. It examines the body of research on issues such as insect nutrition and food safety, the use of insects as animal feed, and the processing and preservation of insects and their products. It highlights the need to develop a regulatory framework to govern the use of insects for food security. And it presents case studies and examples from around the world. Edible insects are a promising alternative to the conventional production of meat, either for direct human consumption or for indirect use as feedstock. To fully realise this potential, much work needs to be done by a wide range of stakeholders. This publication will boost awareness of the many valuable roles that insects play in sustaining nature and human life, and it will stimulate debate on the expansion of the use of insects as food and feed.
Book Synopsis Spark for Python Developers by : Amit Nandi
Download or read book Spark for Python Developers written by Amit Nandi and published by Packt Publishing. This book was released on 2015-12-24 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise guide to implementing Spark Big Data analytics for Python developers, and building a real-time and insightful trend tracker data intensive appAbout This Book• Set up real-time streaming and batch data intensive infrastructure using Spark and Python• Deliver insightful visualizations in a web app using Spark (PySpark)• Inject live data using Spark Streaming with real-time eventsWho This Book Is ForThis book is for data scientists and software developers with a focus on Python who want to work with the Spark engine, and it will also benefit Enterprise Architects. All you need to have is a good background of Python and an inclination to work with Spark.What You Will Learn• Create a Python development environment powered by Spark (PySpark), Blaze, and Bookeh• Build a real-time trend tracker data intensive app• Visualize the trends and insights gained from data using Bookeh• Generate insights from data using machine learning through Spark MLLIB• Juggle with data using Blaze• Create training data sets and train the Machine Learning models• Test the machine learning models on test datasets• Deploy the machine learning algorithms and models and scale it for real-time eventsIn DetailLooking for a cluster computing system that provides high-level APIs? Apache Spark is your answer—an open source, fast, and general purpose cluster computing system. Spark's multi-stage memory primitives provide performance up to 100 times faster than Hadoop, and it is also well-suited for machine learning algorithms.Are you a Python developer inclined to work with Spark engine? If so, this book will be your companion as you create data-intensive app using Spark as a processing engine, Python visualization libraries, and web frameworks such as Flask.To begin with, you will learn the most effective way to install the Python development environment powered by Spark, Blaze, and Bookeh. You will then find out how to connect with data stores such as MySQL, MongoDB, Cassandra, and Hadoop.You'll expand your skills throughout, getting familiarized with the various data sources (Github, Twitter, Meetup, and Blogs), their data structures, and solutions to effectively tackle complexities. You'll explore datasets using iPython Notebook and will discover how to optimize the data models and pipeline. Finally, you'll get to know how to create training datasets and train the machine learning models.By the end of the book, you will have created a real-time and insightful trend tracker data-intensive app with Spark.Style and approach This is a comprehensive guide packed with easy-to-follow examples that will take your skills to the next level and will get you up and running with Spark.
Book Synopsis Python for Everybody by : Charles R. Severance
Download or read book Python for Everybody written by Charles R. Severance and published by . This book was released on 2016-04-09 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics: Exploring Information".There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.
Book Synopsis Machine Learning and Security by : Clarence Chio
Download or read book Machine Learning and Security written by Clarence Chio and published by "O'Reilly Media, Inc.". This book was released on 2018-01-26 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself! With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions
