Build fast and effective applications using Masonite, a Python-based framework. This book covers creating a digital home assistant application, but it’s certainly not the only kind of application you could build. By working on this kind of project, you’ll cover the broad range of topics and requirements you’re likely to find as you establish your own web empire.
You’ll see how Masonite is a developer-centric Python framework, which provides all the tools you’ll need to build powerful and maintainable web applications. After reading and using this book, you’ll have the tools to make and deploy your own web ecommerce application from scratch using the Masonite framework.
What You Will Learn
Who This Book Is For
Web developers new to the Masonite framework. Some prior Python experience is helpful but is not required.
ID: SC - 1447
You’ll start by reviewing the beginning steps of GUI development from, using different projects in every chapter to teach new widgets or concepts that will help you to build better UIs. As you follow along, you will construct more elaborate GUIs, covering topics that include storing data using the clipboard, graphics and animation, support for SQL databases, and multithreading applications. Using this knowledge, you’ll be able to build a photo editor, games, a text editor, a working web browser and an assortment of other GUIs.
Beginning PyQt will guide you through the process of creating UIs to help you bring your own ideas to life. Learn what is necessary to begin making your own applications and more with PyQt!
What You’ll Learn
Understand and implement big data analysis solutions in pandas with an emphasis on performance. This book strengthens your intuition for working with pandas, the Python data analysis library, by exploring its underlying implementation and data structures.
Thinking in Pandas introduces the topic of big data and demonstrates concepts by looking at exciting and impactful projects that pandas helped to solve. From there, you will learn to assess your own projects by size and type to see if pandas is the appropriate library for your needs. Author Hannah Stepanek explains how to load and normalize data in pandas efficiently, and reviews some of the most commonly used loaders and several of their most powerful options. You will then learn how to access and transform data efficiently, what methods to avoid, and when to employ more advanced performance techniques. You will also go over basic data access and munging in pandas and the intuitive dictionary syntax. Choosing the right DataFrame format, working with multi-level DataFrames, and how pandas might be improved upon in the future are also covered.
By the end of the book, you will have a solid understanding of how the pandas library works under the hood. Get ready to make confident decisions in your own projects by utilizing pandas―the right way.
What You Will Learn
ID: SC - 1429
Readers will not only tackle exercises using built-in data structures, but also more advanced techniques, such as functional programming, object-oriented programming, iterators, and generators. With each engaging challenge, readers will practice a new skill and learn how to apply it to everyday coding tasks.
ID: SC - 1412
Written in a fun, accessible and engaging style, this book will
introduce you to the Python language with fully worked examples of
Python code drawn from all aspects of life sciences, including
bioinformatics, structural biology, developmental biology, and
evolutionary biology and ecology.
Using familiar examples designed specifically for life scientists,
you'll learn the basics of the language from the very first chapters and
progress from there. You'll find out how to use Python to automate lab
calculations, search for gene promoter sequences, rotate a molecular
bond, build a cellular toggle switch, model animal coat pattern
formation, grow a virtual plant, simulate a flu epidemic, or evolve
populations.
Python for the Life Sciences provides the tools, confidence and
inspiration to start crafting your own Python solutions for the
challenges you face in your research. If you are a life scientist
interested in learning Python to jump-start your research, this book is
for you.
What You'll Learn
• Write Python scripts to automate your lab calculations
• Search for important motifs in genome sequences
• Use object-oriented programming with Python
• Study mining interaction network data for patterns
• Review dynamic modeling of biochemical switches
Who This Book Is For
Life scientists with little or no programming experience, including
undergraduate and graduate students, postdoctoral researchers in
academia and industry, medical professionals, and teachers/lecturers.
ID: SC - 1410
You’ll start with an introduction to machine learning, highlighting the differences between supervised, semi-supervised and unsupervised learning. In the following chapters you’ll study regression and classification problems, mathematics behind them, algorithms like Linear Regression, Logistic Regression, Decision Tree, KNN, Naïve Bayes, and advanced algorithms like Random Forest, SVM, Gradient Boosting and Neural Networks. Python implementation is provided for all the algorithms. You’ll conclude with an end-to-end model development process including deployment and maintenance of the model.After reading Supervised Learning with Python you’ll have a broad understanding of supervised learning and its practical implementation, and be able to run the code and extend it in an innovative manner.
What You’ll Learn
You`ll review the different types of sensors and sensor networks, along with new technology, including how to build a simple XBee network. You`ll then walk through building an sensor nodes on the XBee, Raspberry Pi, and Arduino, and also learn how to collect data from multiple sensor nodes. The book also explores different ways to store sensor data, including writing to an SD card, sending data to the cloud, and setting up a Raspberry Pi MySQL server to host your data. You`ll even learn how to connect to and interact with a MySQL database server directly from an Arduino! Finally you`ll see how to put it all together by connecting your sensor nodes to your new Raspberry Pi database server.
If you want to see how well XBee, Raspberry Pi, and Arduino can get along, especially to create a sensor network, then Beginning Sensor Networks with XBee, Raspberry Pi, and Arduino is just the book you need.
What You`ll Learn
Code your sensor nodes with Python and MicroPython
Work with new XBee 3 modules
Host your data on Raspberry Pi
Get started with MySQL
Create sophisticated sensor networks
Who This Book Is For
Those interested in building or experimenting with sensor networks and IoT solutions, including those with little or no programming experience. A secondary target includes readers interested in using XBee modules with Raspberry Pi and Arduino, those interested in controlling XBee modules with MicroPython.
ID: SC - 1403
A long journey is really a lot of little steps. The same is true when you’re learning Python, so you may as well have some fun along the way! Written in a lighthearted style with entertaining exercises that build powerful skills, Tiny Python Projects takes you from amateur to Pythonista as you create 19 bitesize programs.
ID: SC - 1391
Python programmers will improve their computer science skills with these useful one-liners.
Python One-Liners will teach you how to read and write “one-liners”: concise statements of useful functionality packed into a single line of code. You’ll learn how to systematically unpack and understand any line of Python code, and write eloquent, powerfully compressed Python like an expert.
The book’s five chapters cover tips and tricks, regular expressions, machine learning, core data science topics, and useful algorithms. Detailed explanations of one-liners introduce key computer science concepts and boost your coding and analytical skills. You’ll learn about advanced Python features such as list comprehension, slicing, lambda functions, regular expressions, map and reduce functions, and slice assignments. You’ll also learn how to:
• Leverage data structures to solve real-world problems, like using
Boolean indexing to find cities with above-average pollution
• Use NumPy basics such as array, shape, axis, type, broadcasting,
advanced indexing, slicing, sorting, searching, aggregating, and
statistics
• Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning
• Create more advanced regular expressions using grouping and named
groups, negative lookaheads, escaped characters, whitespaces, character
sets (and negative characters sets), and greedy/nongreedy operators
• Understand a wide range of computer science topics, including
anagrams, palindromes, supersets, permutations, factorials, prime
numbers, Fibonacci numbers, obfuscation, searching, and algorithmic
sorting
By the end of the book, you’ll know how to write Python at its most refined, and create concise, beautiful pieces of “Python art” in merely a single line.
ID: SC - 1390
Create, execute, modify, and share machine learning applications with
Python and TensorFlow 2.0 in the Jupyter Notebook environment. This book
breaks down any barriers to programming machine learning applications
through the use of Jupyter Notebook instead of a text editor or a
regular IDE.
ID: SC - 1363
