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.
Michael Lopp, or Rands, as he is commonly known online, has been sharing his knowledge as a software manager for years, mainly through his blog. He is one of the most insightful voices about the art of management in a software environment, and even if you are not a manager yourself (and don’t want to become one), will make you understand and better collaborate with your own manager, and be ready when you need to lead a team or understand how it is to work with other humans.
Managing Humans is a selection of the best essays from Michael Lopp's popular website Rands in Repose(www.randsinrepose.com). Lopp is one of the most sought-after IT managers in Silicon Valley, and draws on his experiences at Apple, Netscape, Symantec, and Borland. This book reveals a variety of different approaches for creating innovative, happy development teams. It covers handling conflict, managing wildly differing personality types, infusing innovation into insane product schedules, and figuring out how to build lasting and useful engineering culture. The essays are biting, hilarious, and always informative.
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…
You know what ages like milk? Programming books. I always cringe when someone glances at my programming bookshelf. Some of those books are so dated, they make me appear out of touch by association. Sometimes, I feel compelled to justify myself. “Yes, that's the first edition of Thinking in Java…I keep it for nostalgic reasons, you know!” Yesterday’s software book is today’s fish and chip wrapper. However, there are exceptions. A few classics stay relevant for years, or even decades. This is a shortlist of software books that might be older than you, but are still very much worth reading.
In my consulting gigs, I come across plenty of clueless remarks. Here's a classic one: “We're falling behind schedule, so let's hire more coders.” Or a more recent gem: “We'll be ten times more productive if we generate code with AI.”
When I encounter such nonsense, I don't facepalm or cringe. Instead, I put on my poker face and drop a quote from The Mythical Man-Month.
In an industry where last year’s book is already outdated, Fred Brooks' collection of essays has been a guiding light for nearly half a century. His aphorisms have become legendary. “The bearing of a child takes nine months, no matter how many women are assigned.” “Adding manpower to a late software project makes it later.” “There is no silver bullet.” The list goes on and on.
John Carmack, one of the greatest programmers of our times, used to revisit this book every year or…
Few books on software project management have been as influential and timeless as The Mythical Man-Month. With a blend of software engineering facts and thought-provoking opinions, Fred Brooks offers insight for anyone managing complex projects. These essays draw from his experience as project manager for the IBM System/360 computer family and then for OS/360, its massive software system. Now, 20 years after the initial publication of his book, Brooks has revisited his original ideas and added new thoughts and advice, both for readers already familiar with his work and for readers discovering it for the first time.
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…
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 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…
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.
Dave is the best teacher of programming and how programming languages (and Python specifically) work that I’ve ever met. He has a knack for making explanations of tough concepts seem clear, and he is very good at focusing on what’s essential to using a coding technique or structure and how to write good code. Like all of Dave’s books, the stuff in here just makes sense.
Expert Insight for Modern Python (3.6+) Development from the Author of Python Essential Reference
The richness of modern Python challenges developers at all levels. How can programmers who are new to Python know where to begin without being overwhelmed? How can experienced Python developers know they're coding in a manner that is clear and effective? How does one make the jump from learning about individual features to thinking in Python at a deeper level? Dave Beazley's new Python Distilled addresses these and many other real-world issues.
Focusing on Python 3.6 and higher, this concise handbook focuses on the essential core…
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.
I like this book not just because it’s a complete guide to the many ins and outs of data cleaning with Python, but also because David lays out the types of problems and the issues behind them. There are always trade-offs in data cleaning and this book lays out those trade-offs better than any other I’ve seen. This is one of the few books that as I go through it, I struggle to think of anything that could have been said better.
Think about your data intelligently and ask the right questions
Key Features
Master data cleaning techniques necessary to perform real-world data science and machine learning tasks
Spot common problems with dirty data and develop flexible solutions from first principles
Test and refine your newly acquired skills through detailed exercises at the end of each chapterBook Description
Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the…
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.
Dane covers the more advanced topics a programmer needs to be successful as a professional. In particular, he has good discussions of the basics of software design – things like separation of concerns, encapsulation, testing, and performance, as well as some of the issues involved with creating and maintaining large-scale systems. This is the book that I wish I’d had early in my coding career.
Summary Professional developers know the many benefits of writing application code that’s clean, well-organized, and easy to maintain. By learning and following established patterns and best practices, you can take your code and your career to a new level. With Practices of the Python Pro, you’ll learn to design professional-level, clean, easily maintainable software at scale using the incredibly popular programming language, Python. You’ll find easy-to-grok examples that use pseudocode and Python to introduce software development best practices, along with dozens of instantly useful techniques that will help you code like a pro.
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.
