Packt Pub: Python - Machine Learning, Deep Learning, Penetration Testing Video Course Collection Free

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Packt Pub: Python - Machine Learning, Deep Learning, Penetration Testing Video Course Collection
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Many programming languages are used today, some are used, and some have gone obsolete. In the last few years, the programming scenario has changed drastically as developers and programmers are searching for more universal and approachable languages. This is the reason why Python language has become so famous recently. The Python community is growing bigger day by day as many programmers are now finding it to be one of the most user-friendly programming languages.

Python language has become so famous that every field and sector is now a user of it. Even though the other programming languages are not losing their fans, Python is increasing its fan base. Therefore, more and more people are now aspiring to learn Python. Some of the reasons why having a certification in Python can be helpful are discussed below:

Machine learning

Today, almost everything runs through algorithms, whether it is a search engine, social media, chat bots, virtual personal assistants, etc. These sophisticated algorithms are the result of machine learning and it has changed the entire technological scenario. With machine learning, the major programming language that is been used is Python, and one can find many libraries dedicated to machine learning only.

Big data

Python is used in data science the most and the professionals in this field are required to have expertise in this programming language. Though there are many other languages like Java, R, etc. which is used for data science, Python remains the favorite. This is because of the diversity it allows in automation technology, along with with the various framework and library available like NumPy, PyBrain, etc.

Web development

There are many websites these days like Reddit which are developed using Python language. The main reason why the Python programming language is used in web development is its speed and effectiveness. Using PHP developing a website can take hours, while using Python will take only a few minutes. Also, there are frameworks and libraries like Django and Flask which make the work much easier.

Community

One of the areas that programmers search for these days is the communities. In these communities, the developers and programmers can connect with others from any part of the world and can share their experiences and technologies. This helps them in learning new things about Python and how to solve various issues that may arise while coding.

Libraries

Libraries are really helpful when it comes to application and website development. One can find any kind of code. Python has a huge number of frameworks and libraries like Flask, Django, NumPy, Scipy, Pandas, Tensorflow, Keras, etc. One needs to concentrate on the logic and objective and the codes are easily available in the libraries.

Simple

Lastly, the biggest reason why programmers use Python is the fact that it is a simple programming language. It is a beginner user-friendly language as it does not require a lot of complex codes and syntaxes which are not understandable. Python has an easy and readable syntax and coding which makes its set-up and usage much easier.

1. Beginning Python​

A beginner’s guide to creating your own application with Python​ Get to know Python’s data structures to enhance good design patterns and scalability to your code Construct loops to perform repeated tasks Create functions in Python to provide programs with better modularity Understand the concept of function recursion adding clarity to write and debug codes Manage program control flow and branching to perform conditional tasks Install third-party libraries to add advanced customizations to images Perform picture manipulations such as contrast and grayscale

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About

Python is becoming the language of choice for pretty much every arena. It is a very simple yet extremely powerful programming language. It is a scripting language that is widely used for prototyping to get work up and running in a short amount of time. This course assumes no programming experience and slowly builds the tools you need to take on larger challenges. Once this is done, we dive into the fundamentals of Python programming with variables, numbers, strings, and so on. You'll learn to make decisions on your programs with conditional statements and discover that Python has the ability to iterate over the items of any sequence such as a list or a string with loops. You will see how functions play a major role to provide a high degree of code reusing. Along with the built-in functions, you will be able to build your own functions as well. When you've done all this, you'll be ready to create modules in Python all by yourself. Finally, you'll enhance your skills by performing some very interesting manipulations on images. Speed up your journey with the Pythonic way of programming. By the end of this course, you will be a mature Python programmer. Make use of the freedom to design programs of your choice and be ready to take your Python skills in any direction that you need. Style and Approach This course is an easy-going and pragmatic approach to learning the ABCs of Python. Each video provides in-depth knowledge on a topic with a number of examples, and throughout the course we keep building your skills to the next level.

Features

Gain expertise in creating a complete application with Python by learning the fundamentals Packed with powerful examples to get you up to speed with the features of Python Get an in-depth coverage of everything you need to know to become a seasoned Python programmer

Beginner Python

2. Python Design Patterns
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Design patterns to improve the speed, code reuse, and performance of your Python applications

Learn	Use creational patterns such as Factory, Builder, and so on Understand which patterns to use during development, and when Identify simple ways to realize relationships between entities Encapsulate behavior in an object and delegate requests to it Understanding design techniques that will be detrimental to your application
About	A knowledge of design patterns enables developers to improve their codebase, promotes code reuse, and makes the architecture more robust. This course focuses on showing you the practical aspects of smarter coding in Python. We start off by easing you into the world of design patterns, and helping you brush up on your OOP skills. From there, you'll explore the most widely used patterns and create objects in a manner best suited to the situation. Then we take you through some patterns that will help you identify simple ways to realize relationships between entities. Next, we show you how to encapsulate behavior in an object and delegate requests to it, before we up the ante and delve into some advanced patterns. Last but not least, we'll make you aware of design styles that will hamper your development, rather than improving it. With this course, thanks to patterns, you will be well equipped to craft faster, cleaner, and smarter applications. Style and Approach The user-friendly video has a practical approach. Every pattern discussed is followed by an important example.
Features	Get familiar with design patterns and their classification Understand different creational patterns and structural patterns A complete guide equipped with key tasks to help you understand design patterns

Python Design Patterns


3. Mastering Python
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Get to grips with Python best practices and advanced tools to design, distribute, and test your programs

Learn	Build Python packages to efficiently create reusable code Become proficient at creating tools and utility programs in Python Use the Git version control system to protect your development environment from unwanted changes Harness the power of Python to automate other software Distribute computation tasks across multiple processors Handle high I/O loads with asynchronous I/O for smoother performance Take advantage of Python's metaprogramming and programmable syntax features Get to grips with unit testing to write better code, faster
About	Python is one of the most powerful, flexible, and popular programming languages in the world. Even though Python programs are simple to work with, writing code that is efficient, maintainable, and reusable can be a little tricky for some. The presence of Python's “batteries included” toolbox allows you to easily produce application prototypes or implement new algorithms with minimum efforts. This course takes you on a journey from the basics of operating in a Python development environment through to advanced topics and master-level techniques. It presents you with a guide to Python and its standard library, focusing on language and library elements that are particularly useful for tool authors and system programmers. We start off with the basics to set up a functioning environment, creating packages, and running them on the command line. Through our journey, we'll highlight the major aspects of managing our Python development environment, handling parallel computation, and mastering asynchronous I/O for improved performance of our system. Finally, we'll learn the secrets of metaprogramming and unit testing in Python arming you with the perfect skillset to be a Python expert. Mastering Python will get you up to speed in everything from basic programming practices to high-end tools and techniques that will help you set apart as a successful Python programmer. Style and Approach This video course is a step-by-step tutorial with each section covering a distinct topic enhanced with discussions and examples; the topics have a wide variety ranging from the basics and fundamentals of Python to advanced power skills.
Features	Explore the immense Python libraries to write efficient, reusable code Create adaptable programs that run on multiple processors with parallel programming Become a Python expert with the help of detailed discussions, illustrated with concrete examples

Mastering Python

4. Python Web Penetration Testing​

Make your applications attack-proof by penetration testing with Python

Learn	Understand the web application penetration testing methodology and toolkit Interact with web applications using Python and the Requests library Write a web crawler/spider with the Scrapy library Create an HTTP bruteforcer based on Requests Create a Password bruteforcer for Basic, NTLM, and Forms authentication Detect and exploit SQL injections vulnerabilities by creating a script all by yourself Intercept and manipulate HTTP communication using Mitmproxy
About	With the huge growth in the number of web applications in the recent times, there has also been an upsurge in the need to make these applications secure. Web penetration testing is the use of tools and code to attack a website or web app in order to assess its vulnerabilities to external threats. While there are an increasing number of sophisticated ready-made tools to scan systems for vulnerabilities, the use of Python allows testers to write system-specific scripts, or alter and extend existing testing tools to find, exploit, and record as many security weaknesses as possible. This course will walk you through the web application penetration testing methodology, showing you how to write your own tools with Python for every main activity in the process. It will show you how to test for security vulnerabilities in web applications just like security professionals and hackers do. The course starts off by providing an overview of the web application penetration testing process and the tools used by professionals to perform these tests. Then we provide an introduction to HTTP and how to interact with web applications using Python and the Requests library. Then will follow the web application penetration testing methodology and cover each section with a supporting Python example. To finish off, we test these tools against a vulnerable web application created specifically for this course. Stop just running automated tools—write your own and modify existing ones to cover your needs! This course will give you a flying start as a security professional by giving you the necessary skills to write custom tools for different scenarios and modify existing Python tools to suit your application’s needs. Style and Approach With a pragmatic approach to learning, this video course will help you build different web application security testing tools. With each section building on the knowledge of the previous section, this course will help you to smartly assess the security needs of your apps.
Features	Become proficient at writing your own tools to identify security vulnerabilities in web applications Take your first steps to becoming a security professional by getting an in-depth understanding of the process behind web application security testing See practical examples of each phase of the web application testing process: Reconnaissance, Mapping, Vulnerability Discovery, and Vulnerability Exploitation

Python Web Penetration



5. Python Machine Learning Projects
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Get up-and-running via Machine Learning with Python's insightful projects

Learn	Explore and use Python's impressive machine learning ecosystem Successfully evaluate and apply the most effective models to problems Learn the fundamentals of NLP—and put them into practice Visualize data for maximum impact and clarity Deploy machine learning models using third-party APIs Get to grips with feature engineering
About	Machine learning gives you unimaginably powerful insights into data. Today, implementations of machine learning have been adopted throughout Industry and its concepts are numerous. This video is a unique blend of projects that teach you what Machine Learning is all about and how you can implement machine learning concepts in practice. Six different independent projects will help you master machine learning in Python. The video will cover concepts such as classification, regression, clustering, and more, all the while working with different kinds of databases. By the end of the course, you will have learned to apply various machine learning algorithms and will have mastered Python's packages and libraries to facilitate computation. You will be able to implement your own machine learning models after taking this course. Style and Approach This video is a combination of six independent projects, each taking a unique dataset, a different problem statement, and a different solution.
Features	Explore the power of Python and create your own machine learning models with this project-based tutorial Get superb insights from your data in different scenarios and deploy machine learning models with ease Learn how to put complex machine learning concepts into practice

Python Machine Learning Projects


6. Deep Learning with Python

Dive into the future of data science and implement intelligent systems using deep learning with Python
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Learn	Get a quick brief about backpropagation Perceive and understand automatic differentiation with Theano Exhibit the powerful mechanism of seamless CPU and GPU usage with Theano Understand the usage and innards of Keras to beautify your neural network designs Apply convolutional neural networks for image analysis Discover the methods of image classification and harness object recognition using deep learning Get to know recurrent neural networks for the textual sentimental analysis model
About	Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in Python. The aim of deep learning is to develop deep neural networks by increasing and improving the number of training layers for each network, so that a machine learns more about the data until it’s as accurate as possible. Developers can avail the techniques provided by deep learning to accomplish complex machine learning tasks, and train AI networks to develop deep levels of perceptual recognition. Deep learning is the next step to machine learning with a more advanced implementation. Currently, it’s not established as an industry standard, but is heading in that direction and brings a strong promise of being a game changer when dealing with raw unstructured data. Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language processing. Developers can avail the benefits of building AI programs that, instead of using hand coded rules, learn from examples how to solve complicated tasks. With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. This course takes you from basic calculus knowledge to understanding backpropagation and its application for training in neural networks for deep learning and understand automatic differentiation. Through the course, we will cover thorough training in convolutional, recurrent neural networks and build up the theory that focuses on supervised learning and integrate into your product offerings such as search, image recognition, and object processing. Also, we will examine the performance of the sentimental analysis model and will conclude with the introduction of Tensorflow. By the end of this course, you can start working with deep learning right away. This course will make you confident about its implementation in your current work as well as further research. Style and Approach An easy-to-follow and structured video tutorial with practical examples and coding with IPython notebooks to help you get to grips with each and every aspect of deep learning.
Features	Gain an insight into the world of deep learning based AI programs Implement automatic image recognition and text analysis models using deep learning Get to know each concept along with its practical implementation

Deep Learning with Python
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Python is a language that has a lot many applications these days, and that is the reason why one should look out for the best course to learn about more about it.

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