Building Machine Learning Systems with Python Third Edition - 2018.pdf
Get more from your data by creating practical machine learning systems with Python
Key Features
- Develop your own Python-based machine learning system
- Discover how Python offers multiple algorithms for modern machine learning systems
- Explore key Python machine learning libraries to implement in your projects
Book Description
Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems.
Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems.
By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks.
What you will learn
- Build a classification system that can be applied to text, images, and sound
- Employ Amazon Web Services (AWS) to run analysis on the cloud
- Solve problems related to regression using scikit-learn and TensorFlow
- Recommend products to users based on their past purchases
- Understand different ways to apply deep neural networks on structured data
- Address recent developments in the field of computer vision and reinforcement learning
Who this book is for
Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Python's machine learning capabilities to develop effective solutions. Prior knowledge of Python programming is expected.
MicroPython for BBC micro:bit Technical Workshop - 2018 pdf
BBC micro:bit is a development board to learn embedded system easily. This book is designed to help you to get started with BBC micro:bit development using MicroPython platform. The following is a list of highlight content in this book.
- * Development environment preparation
- * Set up MicroPython on BBC micro:bit Board
- * Display Programming
- * BBC micro:bit GPIO
- * Reading Analog Input and PWM
- * Working with SPI
- * Working with I2C
- * Working with Accelerator and Compass Sensors
Django - The Easy Way pdf - 2017 PDF
Django is a very powerful Python Web Framework. You can use it to build everything from simple websites to big high traffic systems.
But starting with Django can be a daunting experience for beginners. The purpose of this book is to guide you through the essential concepts with pragmatic step-by-step examples. You will learn how to build a complete website and deploy it in a real world production environment.
The focus is on Django basic concepts so covering other technologies is kept at minimum. It’s helpful to know some Python, HTML, and CSS but you don’t need to have any previous experience with those or web development in general to be able to follow the book.
You will learn things like:
- How to setup PyCharm for Django (you can use any editor).
- How to organize the project and add a base app to hold common assets.
- How template inheritance works.
- How to reuse common template items like grids and pagination.
- How to work with models, views and urls.
- How to use GIT and Bitbucket to version control and deploy your code.
- How to style all features with SASS (or CSS) and Gulp.
- How to create a responsive design.
- How to generate thumbnails.
- How to use relationships (ManyToMany, OneToMany and Foreignkey) in practical contexts.
- How to create custom forms to add and edit content.
- How to create and extend class based views.
- How to create a custom search.
- How to create an authentication system (sign-in, login, logout and reset password).
- How to restrict access with groups, permissions and decorators.
- How to add a user profile page.
- How to add inline fields to the admin area.
- How to do test driven development (TDD).
- How to translate the website.
- How to create custom error pages.
- How to setup a production environment with Digitalocean, PostgreSQL, Nginx and Gunicorn.
- How to use fixtures to apply initial data.
- How to setup domain, HTTPS, Email and Caching with Memcached.
- … and a lot more.
