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Podcasts
Sebastian Raschka, Vahid Mirjalili
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.
From banking and manufacturing through to education and entertainment, using data science for business has revolutionized almost every sector in the modern world. It has an important role to play in everything from app development to network security.Taking an interactive approach to learning the fundamentals, this book is ideal for beginners. You’ll learn all the best practices and techniques for applying data science in the context of real-world scenarios and examples.Starting with an introduction to data science and machine learning, you’ll start by getting to grips with Jupyter functionality and features. You’ll use Python libraries like sci-kit learn, pandas, Matplotlib, and Seaborn to perform data analysis and data preprocessing on real-world datasets from within your own Jupyter environment. Progressing through the chapters, you’ll train classification models using sci-kit learn, and assess model performance using advanced validation techniques. Towards the end, you’ll use Jupyter Notebooks to document your research, build stakeholder reports, and even analyze web performance data.By the end of The Applied Data Science Workshop, you’ll be prepared to progress from being a beginner to taking your skills to the next level by confidently applying data science techniques and tools to real-world projects.
In today's techno-savvy world, more and more parts of our lives are going digital, and all this information is accessible anytime and anywhere using mobile devices. It is of the utmost importance that you understand and implement security in your apps that will reduce the likelihood of hazards that will wreck your users' experience.Android Application Security Essentials takes a deep look into Android security from kernel to the application level, with practical hands-on examples, illustrations, and everyday use cases. This book will show you how to overcome the challenge of getting the security of your applications right.Android Application Security Essentials will show you how to secure your Android applications and data. It will equip you with tricks and tips that will come in handy as you develop your applications.We will start by learning the overall security architecture of the Android stack. Securing components with permissions, defining security in a manifest file, cryptographic algorithms and protocols on the Android stack, secure storage, security focused testing, and protecting enterprise data on your device is then also discussed in detail. You will also learn how to be security-aware when integrating newer technologies like NFC and mobile payments into your Android applications.At the end of this book, you will understand Android security at the system level all the way to the nitty-gritty details of application security for securing your Android applications.
Accelerating DevSecOps on AWS. Create secure CI/CD pipelines using Chaos and AIOps
Continuous integration and continuous delivery (CI/CD) has never been simple, but these days the landscape is more bewildering than ever; its terrain riddled with blind alleys and pitfalls that seem almost designed to trap the less-experienced developer. If you’re determined enough to keep your balance on the cutting edge, this book will help you navigate the landscape with ease.This book will guide you through the most modern ways of building CI/CD pipelines with AWS, taking you step-by-step from the basics right through to the most advanced topics in this domain.The book starts by covering the basics of CI/CD with AWS. Once you’re well-versed with tools such as AWS Codestar, Proton, CodeGuru, App Mesh, SecurityHub, and CloudFormation, you’ll focus on chaos engineering, the latest trend in testing the fault tolerance of your system. Next, you’ll explore the advanced concepts of AIOps and DevSecOps, two highly sought-after skill sets for securing and optimizing your CI/CD systems. All along, you’ll cover the full range of AWS CI/CD features, gaining real-world expertise.By the end of this AWS book, you’ll have the confidence you need to create resilient, secure, and performant CI/CD pipelines using the best techniques and technologies that AWS has to offer.