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Showing posts with label Mastering. Show all posts

Monday, September 14, 2015

Udemy – Mastering Python - Networking and Security

Learn the ins and outs of scripting in Python and how to work with Python libraries for networking and forensics.

In this advanced course, you"ll first learn how to create, run, and troubleshoot scripts with Python and then move through specific programming libraries and technologies that allow you to tackle several networking tasks and security measures. No experience is required, although any programming knowledge would be an asset.

You will start with an overview of Python, including how to create and run scripts, use threads, and handle exceptions. From there, Ric will teach you how to network, including how to use the Python libraries for network scripting and develop basic scripts with network functionality. This video tutorial will also cover HTTP programming, security scripting, and forensic scripting. Finally, you will learn about Twisted Python, including the Echo server and HTTP client. Once you have completed the course, you will be fully capable of debugging and security testing using Python, as well as writing Python scripts. Working files are included, allowing you to follow along with the author throughout the lessons.

What are the requirements?

some basic knowledge of programming is recommended, but not required

What am I going to get from this course?

Over 75 lectures and 5 hours of content!

create, run, and debug Python scripts and apply that knowledge to handling common networking and forensics tasks

use Python to interact with MySQL databases and execute commands

What is the target audience?

anyone who wants to dig deeper into Python and its networking-specific libraries

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Saturday, September 12, 2015

Mastering Puppet

Puppet is a configuration management system written for system administrators to manage a large number of systems efficiently and help maintain order.

Pull the strings of Puppet to configure enterprise-grade environments for performance optimization

Overview

Implement puppet in a medium to large installation.

Deal with issues found in larger deployments, such as scaling, and improving performance.

Step by step tutorial to utilize Puppet efficiently to have a fully functioning Puppet infrastructure in an enterprise- level environment

In Detail

Mastering Puppet deals with the issues faced in larger deployments such as scaling and duplicate resource definitions. It will show you how to fit Puppet into your organization and keep everyone working. The concepts presented can be adapted to suit any size organization. This book starts with setting up and installing Puppet in your organization and then moves on to implementing version control in Puppet, creating custom modules, and extending your Puppet infrastructure. Finally, you will learn tips and tricks that are useful when troubleshooting Puppet and the best practices to make you a pro.

What you will learn from this book

Scale out your Puppet masters using proxy techniques

Automate Puppet master deployment using Git Hooks, r10k, and librarian-puppet

Access public modules from Git Forge and use them to solve real-world problems

Use Hiera and ENC to automatically assign modules to nodes

Create custom modules, facts, and types

Use exported resources to orchestrate changes across the enterprise

Approach

Presented in an easy-to-follow, step-by-step tutorial format and packed with examples, this book will lead you through making the best out of Puppet in an enterprise environment.

Who this book is written for

If you are a system administrator or developer who has used Puppet in production and are looking for ways to easily use Puppet in an enterprise environment, this book is for you. This book assumes an intermediate knowledge of Puppet and is intended for those writing modules or deploying Puppet in an enterprise environment.

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Sunday, September 6, 2015

Mastering Python for Data Science

If you are a Python developer who wants to master the world of data science then this book is for you. Some knowledge of data science is assumed.

Explore the world of data science through Python and learn how to make sense of data

About This Book

Master data science methods using Python and its libraries

Create data visualizations and mine for patterns

Advanced techniques for the four fundamentals of Data Science with Python – data mining, data analysis, data visualization, and machine learning

What You Will Learn

Manage data and perform linear algebra in Python

Derive inferences from the analysis by performing inferential statistics

Solve data science problems in Python

Create high-end visualizations using Python

Evaluate and apply the linear regression technique to estimate the relationships among variables.

Build recommendation engines with the various collaborative filtering algorithms

Apply the ensemble methods to improve your predictions

Work with big data technologies to handle data at scale

In Detail

Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving.

This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science.

Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods.

Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics.

Style and approach

This book is an easy-to-follow, comprehensive guide on data science using Python. The topics covered in the book can all be used in real world scenarios.

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