Designing Machine Learning Systems with PythonMachine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles.
There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it ...
Python Projects for KidsKids are always the most fast-paced and enthusiastic learners, and are naturally willing to build stuff that looks like magic at the end (when it works!). Programming can be one such magic. Being able to write a program that works helps them feel they've really achieved something. Kids today are very tech-savvy and cannot wait to enter the fast-paced digital world.
Because Python is one of the most popular languages and has a syntax that is quite simple to understand, even kids are eager to use it as a stepping stone to learning programming languages.
This book will cover projects that are simple and fun, and teach kids how to write Python code that works.
The book will teach the basics of Python programming, installation, and so on and then will move on to projects. A total of three projects, with each and every step explained carefully, without any assumption of previous experience. ...
Foundations for Analytics with PythonMany of Excel's 750 million users would like to do more with their data, such as repeating similar analyses over hundreds of files or combining the data in many files for analysis at one time. This practical guide shows ambitious non-programmers how to automate and scale data processing and analysis of different data formats with Python using business-relevant examples with complete, easy-to-read code.
Beginning with the basics of Python author Clinton Brownley shows you how to deal with Excel, CSV, and text files in Python leading up to scheduling scripts to automatically gather and process information without human intervention. More practical than many other introductions to Python this book gives you skills you can immediately apply in your job. ...
Expert Python Programming, 2nd EditionPython is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge.
The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code.
You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily.
You will also be using some powerful tools such as buildout and vitualenv to release and deplo ...
Internet of Things with PythonInternet of Things (IoT) is revolutionizing the way devices/things interact with each other. And when you have IoT with Python on your side, you'll be able to build interactive objects and design them.
This book lets you stay at the forefront of cutting-edge research on IoT. We'll open up the possibilities using tools that enable you to interact with the world, such as Intel Galileo Gen 2, sensors, and other hardware. You will learn how to read, write, and convert digital values to generate analog output by programming Pulse Width Modulation (PWM) in Python. You will get familiar with the complex communication system included in the board, so you can interact with any shield, actuator, or sensor.
Later on, you will not only see how to work with data received from the sensors, but also perform actions by sending them to a specific shield. You'll be able to connect your IoT device to the entire world, by integrating WiFi, Bluetooth, and Internet settings. With everything rea ...
Introduction to Machine Learning with PythonMany Python developers are curious about what machine learning is and how it can be concretely applied to solve issues faced in businesses handling medium to large amount of data. Introduction to Machine Learning with Python teaches you the basics of machine learning and provides a thorough hands-on understanding of the subject.
You'll learn important machine learning concepts and algorithms, when to use them, and how to use them. The book will cover a machine learning workflow: data preprocessing and working with data, training algorithms, evaluating results, and implementing those algorithms into a production-level system. ...
Python Data Analysis CookbookData analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning.
Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You'll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining.
In this book, you will dive deeper into r ...
Mastering PythonPython is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward.
This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also ...
Learn to Program with PythonGet started in the world of software development: go from zero knowledge of programming to comfortably writing small to medium-sized programs in Python. Programming can be intimidating (especially when most books on software require you to know and use obscure command line instructions) but it doesn't have to be that way!
In Learn to Program with Python author Irv Kalb uses his in-person teaching experience to guide you through learning the Python computer programming language. He uses a conversational style to make you feel as though he is your personal tutor. All material is laid out in a thoughtful manner, each lesson building on previous ones. Many real–world analogies make the material easy to relate to. A wide variety of well-documented examples are provided. Along the way, you'll develop small programs on your own through a series of coding challenges that reinforce the content of the chapters. ...
Text Analytics with PythonDerive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization.
Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems.
Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure; Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and tex ...
Think DSPIf you understand basic mathematics and know how to program with Python you're ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they're applied in the real world. In the first chapter alone, you'll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds.
Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material.
You'll explore: Periodic signals and their spectrums; Harmonic structure of simple waveforms; Chirps and other sounds whose spectrum changes over time; Noise signals and natural sources of noise; The autocorrelation function for estimating pitch; The discrete cosine transform (DCT) for compression; The Fast Fourier Transform for spectral analysis; Relati ...