Learn how to create interactive and visually aesthetic plots using the Bokeh package in Python Key Features * * A step by step approach to creating interactive plots with Bokeh * Go from nstallation ...all the way to deploying your very own Bokeh application * Work with a real time datasets to practice and create your very own plots and applications Book Description Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization. The book starts out by helping you understand how Bokeh works internally and how you can set up and install the package in your local machine. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data. Finally you will use all the concepts that you have learned in the previous chapters to create your very own Bokeh application from scratch. By the end of the book you will be able to create your very own Bokeh application. You will have gone through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with interactive and visually aesthetic plots. What you will learn * * Installing Bokeh and understanding its key concepts * Creating plots using glyphs, the fundamental building blocks of Bokeh * Creating plots using different data structures like NumPy and Pandas * Using layouts and widgets to visually enhance your plots and add a layer of interactivity * Building and hosting applications on the Bokeh server * Creating advanced plots using spatial data Who this book is for This book is well suited for data scientists and data analysts who want to perform interactive data visualization on their web browsers using Bokeh. Some exposure to Python programming will be helpful, but prior experience with Bokeh is not required.
This book is designed for use as aprimary introduction to Python and can be used as an introductory text or as aresource for professionals in industry. The book has been divided into foursections. ...The first section deals with the language fundamentals, primarily theprocedural part of the language, the second introduces the object-oriented paradigms,the third section deals with data structures, and the last is devoted toadvanced topics like handling multi-dimensional arrays using NumPy andvisualization using Matplotlib. Regular expressions and multi-threading havebeen introduced in the appendices.FEATURESIncludes sections dedicated to data structures Offers in-depth treatment of topics such as classes, inheritance, BST, andNumPyIntroduces topics like Matplotlib and PILContains exercises for practice and a review of essential programming concepts
Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a ...strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek.
If you want to develop complete Python web apps with Django, then this Learning Path is for you. You will walk through Python programming techniques, and them implement them for creating four ...professional Django projects, teaching you how to solve common problems and develop RESTful web services with Django and Python. You will learn how to.
Master Python scripting to build a network and perform security operations Key Features * Learn to handle cyber attacks with modern Python scripting * Discover various Python libraries for building ...and securing your network * Understand Python packages and libraries to secure your network infrastructure Book Description It's becoming more and more apparent that security is a critical aspect of IT infrastructure. A data breach is a major security incident, usually carried out by just hacking a simple network line. Increasing your network's security helps step up your defenses against cyber attacks. Meanwhile, Python is being used for increasingly advanced tasks, with the latest update introducing many new packages. This book focuses on leveraging these updated packages to build a secure network with the help of Python scripting. This book covers topics from building a network to the different procedures you need to follow to secure it. You'll first be introduced to different packages and libraries, before moving on to different ways to build a network with the help of Python scripting. Later, you will learn how to check a network's vulnerability using Python security scripting, and understand how to check vulnerabilities in your network. As you progress through the chapters, you will also learn how to achieve endpoint protection by leveraging Python packages along with writing forensic scripts. By the end of this book, you will be able to get the most out of the Python language to build secure and robust networks that are resilient to attacks. What you will learn * Develop Python scripts for automating security and pentesting tasks * Discover the Python standard library's main modules used for performing security-related tasks * Automate analytical tasks and the extraction of information from servers * Explore processes for detecting and exploiting vulnerabilities in servers * Use network software for Python programming * Perform server scripting and port scanning with Python * Identify vulnerabilities in web applications with Python * Use Python to extract metadata and forensics Who this book is for This book is ideal for network engineers, system administrators, or any security professional looking at tackling networking and security challenges. Programmers with some prior experience in Python will get the most out of this book. Some basic understanding of general programming structures and Python is required.
Python is currently used in many different areas. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After ...reading this book, readers will understand these problems, and more importantly, understand how to correct them.
This book teaches you to leverage deep learning models in performing various NLP tasks along with showcasing the best practices in dealing with the NLP challenges. The book equips you with practical ...knowledge to implement deep learning in your linguistic applications using NLTk and Python's popular deep learning library, TensorFlow.
Become a master at penetration testing using machine learning with Python Key Features * Identify ambiguities and breach intelligent security systems * Perform unique cyber attacks to breach robust ...systems * Learn to leverage machine learning algorithms Book Description Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it's important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you've gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you'll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you'll focus on topics such as network intrusion detection and AV and IDS evasion. We'll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system. By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system. What you will learn * Take an in-depth look at machine learning * Get to know natural language processing (NLP) * Understand malware feature engineering * Build generative adversarial networks using Python libraries * Work on threat hunting with machine learning and the ELK stack * Explore the best practices for machine learning Who this book is for This book is for pen testers and security professionals who are interested in learning techniques to break an intelligent security system. Basic knowledge of Python is needed, but no prior knowledge of machine learning is necessary.
Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, ...and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand. This book comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language. The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks. The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation
