I’ve been teaching and writing Python code (and managing others while they write Python code) for over 20 years. After all that time Python is still my tool of choice, and many times Python is the key part of how I explore and think about problems. My experience as a teacher also has prompted me to dig in and look for the simplest way of understanding and explaining the elegant way that Python features fit together.
Luciano’s book is one of the most complete discussions of the ins and outs of Python that I’ve seen. He is fascinated by coding in general and it comes across as he explores the ways Python is similar to (and different from) other language paradigms. This is the book I take out if I’m starting to dig in and explore a feature of Python, and if you want to understand the details beneath the details, this is the book for you.
Learn how to write idiomatic, effective Python code by leveraging its best features. Python's simplicity quickly lets you become productive with it, but this often means you aren't using everything the language has to offer. By taking you through Python's key language features and libraries, this practical book shows you how to make your code shorter, faster, and more readable all at the same time--what experts consider "Pythonic."Many programmers who learn Python basics fall into the trap of reinventing the wheel because of past experience in other languages, and try to bend the language to patterns that don't really apply…
I’ve been teaching and writing Python code (and managing others while they write Python code) for over 20 years. After all that time Python is still my tool of choice, and many times Python is the key part of how I explore and think about problems. My experience as a teacher also has prompted me to dig in and look for the simplest way of understanding and explaining the elegant way that Python features fit together.
Al is one of the clearest writers on Python that I know. Here he distills his experience as both a working software engineer and a successful author to take coders from advanced beginner/intermediate level on to all of the “extra” knowledge one needs to write good code for practical use. When I read this book I find myself wishing I could write with such simplicity.
You're a student who wants to jumpstart their career with practical skills, or you're a self-taught beginner who has learned all you can from beginner programmer books and coding bootcamps. Now you're looking for the next step to becoming a real-world professional programmer so you can create your own apps and get started with your career. If that fits, then this book is for you! This book is perfect for self-taught programmers looking for the stuff intro books don't teach you and students wanting to get practical information before getting started with applying their new programming skills.
I have been building real-time, production machine learning models for over 20 years. My book, and my book recommendations, are informed by that experience. I have a lot of empathy for people who are new to machine learning because I’ve taught courses on the topic. I founded the Advanced Solutions Lab at Google where we helped data scientists working for Google Cloud customers (who already knew ML) become ML engineers capable of building reliable ML models. The first two are the books I’d recommend today to newcomers and the last three to folks attending the ASL.
There are three types of machine learning books — books written for people who want to become machine learning engineers, books written for people who want to become machine learning researchers, and books written for business executives. Reading a book written for researchers or executives can be a frustrating experience if you are a software engineer, social scientist, or mechanical engineer who wants to learn machine learning and get an ML job in the industry.
If you are a coder who wants to become an ML engineer, you have got to learn machine learning concepts, but you want to learn them in a practical way. You need a book that leads with intuition and shows you implementations with code. It has to do this without getting sidetracked into ML theory, getting mired in statistical concepts, or being so superficial that you don’t understand why the code works.…
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.
By using concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow-author Aurelien Geron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help…
My life has been about programming for as long as I can remember. Learning to code was a way to connect with my dad and express my creativity at a young age. Since I grew up with code, it became the way I understood the world; often I could look at a process or program and immediately see its source code in my mind. I developed a very strong sense of aesthetics searching for “perfect code,” which for me was code that was not only error-free but resistant to errors. My studies, research, and career is about moving myself and all programmers closer to that goal: Software that never fails.
Continuing down the engineering part of this mini-curriculum, we have a collection of interesting ideas, each written by a different author, all of them inspiring.
Some of the chapters in this book I have reread more times than I can count, because the ideas are so original and intriguing that my fingers start to tingle.
How do the experts solve difficult problems in software development? In this unique and insightful book, leading computer scientists offer case studies that reveal how they found unusual, carefully designed solutions to high-profile projects. You will be able to look over the shoulder of major coding and design experts to see problems through their eyes. This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things. The authors think aloud as they work through their project's architecture, the tradeoffs made in its construction, and when it was important to…
I’ve been dabbling in Python for the last 22 years. I am a regular speaker at Pycon India ever since its inception. Most of my talks are related to Django. I host arunrocks.com where I write tutorials, and articles and publish screencasts on several Django and Python topics. My initial screencast titled "Building a blog in 30 mins with Django" is one of the most popular screencasts for beginners in Django. I’m a developer member of the Django Software Foundation.
A beginner-friendly book with very clear writing. Vincent has several books on Django aimed at different levels of expertise. This one has a clear and instructional approach to building simple web applications. It is a little light on concepts and explanation of the requirements, probably intentionally, for which you can rely on other books.
Django for Beginners is a project-based introduction to Django, the popular Python-based web framework. Suitable for total beginners who have never built a website before as well as professional programmers looking for a fast-paced guide to modern web development and Django fundamentals.
In the book you’ll learn how to:
Build 5 websites from scratch, including a Blog and Newspaper website
Deploy online using security best practices
Customize the look and feel of your sites
Write tests and run them for all your code
Integrate user authentication, email, and custom user models
Add permissions and authorizations…
I am motivated by working on products that many people use. I've been a part of companies that deliver products impacting millions of people. To achieve it, I am working in the Big Data ecosystem and striving to simplify it by contributing to Dremio's Data LakeHouse solution. I worked on projects using Spark, HDFS, Cassandra, and Kafka technologies. I have been working in the software engineering industry for ten years now, and I've tried to share my experience and lessons learned in the Software Mistakes and Tradeoffs book, hoping that it will allow current and the next generation of engineers to create better software, leading to more happy users.
The Hands-on Machine Learning book presents an end-to-end approach to many problems that can be solved with machine learning.
Every concept and topic is backed up with a running code that you can experiment with and adapt to your real-world problems.
Thanks to this book, you will be able to understand the state of the art of today's machine learning and feel comfortable using the most up-to-date ML methods.
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.
With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout…
Some programmers learn through online articles, videos, and blog posts. Not me. I need a throughline—a consistent, expert distillation of the material to take me from where I am to where I want to be. I am not good at patching together information from disparate sources. I need a great book. I have a PhD in computer science education, and I want to know what helps people learn. More importantly, I want to know how we can use such discoveries to write more effective books. The books I appreciate most are those that demonstrate not only mastery of the subject matter but also mastery of teaching.
Learning how to program in Python and make a video game at the same time. Hmm – sounds like learning your native language while writing a novel. That could be messy. Could be – but not with this book. McManus knows video games. McManus knows how to teach. I love the idea of teaching a programming language through one extended context. If, like me, you’re fascinated by retro video games, get this book and let that fascination propel you through your beginning programming journey. Bonus feature: commitment to the bit; everything is in space!
Launch into coding with Mission: Python, a space-themed guide to building a complete computer game in Python. As you work through the book, you'll build exercises and mini-projects, like making a spacewalk simulator and creating an astronaut's safety checklist that will put your new Python skills to the test. Before you know it, you'll have a working, awesome game to stump your friends with (and some nifty coding skills, too!). You can follow this book using a Raspberry Pi or a Microsoft Windows PC, and the 3D graphics and sound effects you need are provided as a download.
Since I was a kid, I’ve been passionate about technology and had a clear vocation to work with computers. I’ve been a developer for more than 20 years now, spending half of them mainly in the Python environment, and I’ve always been interested in improving my skills. While it’s true that software development is a field that changes constantly and technology evolves at great speed, there are some elements that remain relatively unchanged and can be used to compound knowledge and ability. In particular, the elements that are closer to the human element, teamwork, coordination, etc. are quite stable over time.
While this is a Python-specific book, it’s a fantastic description of all the possibilities for testing with a powerful module like Pytest offers. Testing is one of the basic experiences for a programmer, as it should be included as a core part of the development process. Understanding all the different options available like mark groups of tests, parametric tests, building your own extensions, or test coverage, to name only a few details, expands the understanding of how to design better tests and run them more efficiently.
Do less work when testing your Python code, but be just as expressive, just as elegant, and just as readable. The pytest testing framework helps you write tests quickly and keep them readable and maintainable - with no boilerplate code. Using a robust yet simple fixture model, it's just as easy to write small tests with pytest as it is to scale up to complex functional testing for applications, packages, and libraries. This book shows you how. For Python-based projects, pytest is the undeniable choice to test your code if you're looking for a full-featured, API-independent, flexible, and extensible testing…
I’ve spent most of my life writing code—and too much of that life teaching new programmers how to write code like a professional. If it’s true that you only truly understand something after teaching it to someone else, then at this point I must really understand programming! Unfortunately, that understanding has not led to an endless stream of bug-free code, but it has led to some informed opinions on programming and books about programming.
This book’s title is absolutely perfect! There’s no agenda here other than identifying things that will make you a more effective and productive programmer.
That leads to a book packed with solid advice, whether it’s about how to write code or how to think about your career. The authors are consultants, so there are plenty of clear and interesting examples drawn from many different problem domains. That’s super fun for someone like me who’s hyper-focused on a single kind of programming.
"One of the most significant books in my life." -Obie Fernandez, Author, The Rails Way
"Twenty years ago, the first edition of The Pragmatic Programmer completely changed the trajectory of my career. This new edition could do the same for yours." -Mike Cohn, Author of Succeeding with Agile , Agile Estimating and Planning , and User Stories Applied
". . . filled with practical advice, both technical and professional, that will serve you and your projects well for years to come." -Andrea Goulet, CEO, Corgibytes, Founder, LegacyCode.Rocks
". . . lightning does strike twice, and this book is proof." -VM…
I’ve been dabbling in Python for the last 22 years. I am a regular speaker at Pycon India ever since its inception. Most of my talks are related to Django. I host arunrocks.com where I write tutorials, and articles and publish screencasts on several Django and Python topics. My initial screencast titled "Building a blog in 30 mins with Django" is one of the most popular screencasts for beginners in Django. I’m a developer member of the Django Software Foundation.
This is a very well-written book that covers some less covered areas like how to write the most minimal Django application or integrating with Tornado server. The book is short and quite engaging. This is not exactly a book for an impatient beginner as it takes time to build the concepts. Also, the book might be a bit dated since it was last updated in 2014.
How can you take advantage of the Django framework to integrate complex client-side interactions and real-time features into your web applications? Through a series of rapid application development projects, this hands-on book shows experienced Django developers how to include REST APIs, WebSockets, and client-side MVC frameworks such as Backbone.js into new or existing projects. Learn how to make the most of Django's decoupled design by choosing the components you need to build the lightweight applications you want. Once you finish this book, you'll know how to build single-page applications that respond to interactions in real time. If you're familiar with…
