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.
I used this book for several years starting in 2013 when the first edition came out. It absolutely holds up today. Learning the Python language (the syntax) is one thing. Learning how to design programs using this syntax is another. We need both but, unfortunately, many books forgo the latter for the former. Not this book! I like the Problem Solving and Worked Example sections: they help learners apply a disciplined, step-by-step strategy to programming projects. There are multiple, varied contexts here as well, which helps capture a broader base of learners. Bonus feature: the Computing & Society boxes.
Python for Everyone, 3rd Edition is an introduction to programming designed to serve a wide range of student interests and abilities, focused on the essentials, and on effective learning. It is suitable for a first course in programming for computer scientists, engineers, and students in other disciplines. This text requires no prior programming experience and only a modest amount of high school algebra. Objects are used where appropriate in early chapters and students start designing and implementing their own classes in Chapter 9. New to this edition are examples and exercises that focus on various aspects of data science.
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.
Two Scoops is the bible of Django development. It has the most detailed coverage of the Django web framework including best practices and tips. The book has a delightful ice cream-based theme including delightful illustrations. There are several editions of this book so make sure you have the latest one. Overall a valuable reference. However, this book might be daunting for an absolute beginner.
Two Scoops of Django 1.11 Will Help You Build Django Projects.
In this book we introduce you to the various tips, tricks, patterns, code snippets, and techniques that we've picked up over the years. We have put thousands of hours into the fourth edition of the book, writing and revising its material to include significant improvements and new material based on feedback from previous editions.
Table of Contents
Chapter 1: Coding Style Chapter 2: The Optimal Django Environment Setup Chapter 3: How To Lay Out Django Projects Chapter 4: Fundamentals of Django App Design Chapter 5: Settings and Requirements Files…
I have been a machine learning engineer applying my ML expertise in computational advertising, and search domain. I am an author of 8 machine learning books. My first book was ranked the #1 bestseller in its category on Amazon in 2017 and 2018 and was translated into many languages. I am also a ML education enthusiast and used to teach ML courses in Toronto, Canada.
This book is more advanced than the first book I recommended. It presents ML theoretical and practical aspects step-by-step from the bottom up. Each chapter elaborates at length on a core building block in the ML life cycle. For example, feature engineering, supervised learning, and model evaluation have their own separate chapters, with intuitive discussions of how they work. Most of the concept is taught through the simple yet powerful Python Module Scikit-Learn so it won’t overburden you with heavy programming. This book will be perfect for practitioners with some understanding of statistics and linear algebra.
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the…
I started my career in neuroscience. I wanted to understand brains. That is still proving difficult, and somewhere along the way, I realized my real motivation was to build things, and I wound up working in AI. I love the elegance of mathematical models of the world. Even the simplest machine learning model has complex implications, and exploring them is a joy.
Of course, this is not the obvious book to recommend for reinforcement learning, but if you are a beginner, then it’s a quick and easy place to start. It’s compact and gets straight into the main algorithms.
It has a good balance between theory and code and will get you up and running quickly.
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice
Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games-such as Go, Atari games, and DotA 2-to robotics.
Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM…
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.
Being able to understand and change reality through our knowledge and skill is literal magic. We’re building systems with so many exciting and unexpected properties that can be exploited and repurposed for both good and evil. I want to keep some of that magic and help people engineer – build great systems that make people’s lives better. I’ve been securing (and breaking) systems, from operating rooms to spaceships, from banks to self-driving cars for over 25 years. The biggest lesson I’ve learned is that if security is not infused from the start, we’re forced to rely on what ought to be our last lines of defense. This list helps you infuse security into your systems.
Loren’s been contributing to security for over 40 years, and this book captures his hard-won wisdom in a way that’s both humble and accessible. It scales from principles and design approaches to in-depth explanations of exactly how things go wrong and how to avoid those problems. (Also, I was honored to write the foreword.)
Designing Secure Software consolidates Loren Kohnfelder's more than twenty years of experience into a concise, elegant guide to improving the security of technology products. Written for a wide range of software professionals, it emphasizes building security into software design early and involving the entire team in the process. The book begins with a discussion of core concepts. The second part, perhaps this book's most important contribution, covers the process of designing and reviewing a software design with security considerations in mind. The final section details the most common coding flaws that create vulnerabilities, making copious use of code snippets written…
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.
Bell is an expert teacher. I like the order of topics; the breakdown of topics into units; the short, targeted lessons in each unit; the varied capstone projects to tie things together; the explicit learning goals; the structured approach to solving problems. The first bit of code that you’ll write is on page 30. Your first complete program is on page 60. What’s up with those first 59 pages, then? Motivation, comparisons to daily life, setup, and building blocks. Things that other authors tend to skip but that may be important for some learners. Bonus feature: “I try not to forget what it’s like to start learning to program from scratch, no matter how many times I teach the course.”
Whether readers want to become a professional software developer, create web sites, analyze scientific data, or just automate tedious business tasks, learning to program is the first step. Fortunately, learning to program doesn't have to be difficult.
Get Programming: Learn to code with Python introduces you to the world of writing computer programs without drowning you in confusing jargon or theory that make getting started harder than it should be. By working through the examples and exercises in 39 bitesize lessons, you'll learn how to code step-by-step by creating your own programs with the beginner-friendly Python language! With crystal-clear illustrations,…
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.
I’m a kid at heart. (My favourite book genre is middle grade fiction.) Don’t be put off by a book with "kids" in the subtitle. And what an ebullient book this is! I unapologetically laugh at this book’s humour. I like the short chapters with measurable progress in each one; I like the easy GUI programming to get us started; I like the computational study of probability and randomness. I could quibble over the order that some topics are introduced, and some of the forward references… but, you know what? I won’t. This author duo gets it. Bonus feature: that sneaky way of introducing mutability in Chapter 2. Bonus feature #2: SkiFree.
Hello World! Third Edition is a fun, easy-to-use guide with copious illustrations and engaging examples. It takes the reader on a playful tour of basic programming concepts and then puts those concepts together to make fun and useful programs. It uses Python, a programming language that is one of the easiest to read, write, and understand. Like the previous two editions, Hello World! Third Edition is not just for kids. While the tone is light and engaging, it doesn't "talk down" to the reader, and beginners of any age will love its readability and sense of humor. Written by Warren…
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.
Building scalable and performant web applications is both an art and a science. This book focused on such techniques and hence goes beyond what most books on Django try to cover. Anyone running a Django site under heavy load will definitely learn a few tips from this book. However, it is light on explanations and expects you to figure out many things from reading the examples.
