10 books on computer vision and cryptocurrency you should read

In our latest Developer Nation Pulse report we shared data on the top five emerging areas of interest to developers.

Around half of developers say they are working on, learning about, or interested computer vision, according to the insights from our Q1 2021 global survey of over 17,000 developers. Similarly, 45% are interested in cryptocurrencies (e.g. Bitcoin).

Recommended computer vision and cryptocurrency books

However, of the developers engaged with computer vision, only 15% are currently working on the technology. Similarly, only 14% are currently working on cryptocurrencies. One in four developers are currently learning about computer vision, while 29% are learning about cryptocurrencies.

So if you belong to these group, the following book recommendations might be just the thing you’ve been looking. This post was created in partnership with our friends at Packt.

Computer Vision books

Modern Computer Vision with PyTorch

Explore deep learning concepts and implement over 50 real-world image applications.

What reviews say:

“I felt the book is very well structured and compiled. Unless you’re looking for something very very specific, you’d be able to find techniques/implementations for any and all types of problems you are working on. They cover algorithms and implementations of basic neural networks, all the way upto RNNs and reinforcement learning with PyTorch. The breadth covered by this book on the number of techniques and algorithms is really amazing.”

Mastering Computer Vision with TensorFlow 2.x

Build advanced computer vision applications using machine learning and deep learning techniques

What reviews say:

“There are many books out there / but this book stands out – very clear explanation of codes and contents, lots of detailed explanations for object detection, classification, visual search, matching and training in cloud.”

PyTorch Computer Vision Cookbook

Over 70 recipes to master the art of computer vision with deep learning and PyTorch 1.x

“This book is good for beginners to learn about writing deep learning model in PyTorch. Book goes from basic linear model to processing videos in PyTorch and covers variety of use cases e.g. use of GANs, Style transfer project.”

Applied Deep Learning and Computer Vision for Self-Driving Cars

Build autonomous vehicles using deep neural networks and behavior-cloning techniques

What reviews say:

“This book is about how to apply deep learning knowledge to solve self-driving car problems. The technologies mainly focus on computer vision areas. It gives readers lots of code samples, which can help readers to understand the concept in each chapter.”

TensorFlow 2.0 Computer Vision Cookbook

Implement machine learning solutions to overcome various computer vision challenges

What reviews say:

“By far, this is one of the best books to understand how to apply deep learning in the field of computer vision. The concepts have been clearly explained. It covers almost everything from image classification, image segmentation, object detection, etc”

Raspberry Pi Computer Vision Programming, Second Edition

Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3

What reviews say:

“This book was very helpful for me because it covers a wide variety of computer vision topics and offers lots of well thought out code examples using Python, opencv, matplotlib, numpy and other computer vision software. I followed his examples on my RPi and found that they helped me get the format and arguments of opencv commands correctly to include little things like commas, parenthesis, brackets, optional arguments and the like.”

Hands-On Image Generation with TensorFlow

A practical guide to generating images and videos using deep learning

What reviews say:

“The book is a great quickstart into representation with neural networks. (I also read it more deeply at times and it is great for that as well. I myself have experience with high-throughput large scale autoencoders with TensorFlow and building Facial Recognition applications. I appreciated this book a lot.)”

Cryptocurrencies books for developers

Practical Artificial Intelligence and Blockchain

A guide to converging blockchain and AI to build smart applications for new economies

What reviews say:

“Addressing such large topics as artificial intelligence and blockchain at best is a very serious endeavor. Whereas blockchain after a decade plus of existence has developed a useful understanding within its marketplace, that is not at all true of artificial intelligence, better just AI. AI is now well beyond 6 decades of existence as a topic and yet remains in an evolving state with much debate and speculation worldwide, especially over ethical and scope issues. So given that the reader of this book may be either one-of or some combination of a professional scientist, a developer or simply someone wanting to learn, then yes, Ganesh Prasad Kumble’s Practical Artificial Intelligence and Blockchain book is both a good and useful read.”

Blockchain Development for Finance Projects

Building next-generation financial applications using Ethereum, Hyperledger Fabric, and Stellar

What reviews say:

“This book is for developers who want to learn blocking technology by building financial applications. Kudos to the author on providing coding examples and following it with explanation. Overall it is a good book on Ethereum development and I would recommend it for anyone who wants to learn Ethereum blockchain by building fintech applications.”

Securing Blockchain Networks like Ethereum and Hyperledger Fabric

Learn advanced security configurations and design principles to safeguard Blockchain networks

What reviews say:

“This book is for blockchain developers, security professionals, and Ethereum and Hyperledger developers who are looking to implement security in blockchain platforms and ensure secure data management using an example-driven approach. Basic knowledge of blockchain concepts will be beneficial.”

Is there a book or expert that you would recommend to others interested in cryptocurrency or computer vision? Do share in the comments.

Our latest developer survey is live. Let us know which emerging technology you’ll be exploring in 2021.

Community Platforms

Decoding development trends: The 17th State of the Developer Nation Report is out

Every six months, the Developer Economics Survey captures the voice of more than 20,000 developers globally. Our surveys engage developers working across mobile, desktop, IoT, cloud, web, game, AR/VR, machine learning development and data science, decoding development trends.

The 17th Developer Economics survey ran between June and  August 2019. The data analysed provided really interesting insights about the different developer profiles out there.

For instance, one in three developers are all-rounders. Only one in five declare themselves as specialists. There are almost four times as many introverts (37%) as extroverts (10%) among developers. This is a significant difference from the 2:1 ratio in favour of extroverts found in the wider community.

We also included several unusual labels, uncovering, for example, that there are double the number of night owl developers than early birds (29% compared to 14%).. What time is it with you right now?

2X night owl developers compared to early birds (29% compared to 14%

Javascript remains the Queen

Looking, into programming language trends we found that JavaScript remains the queen with a community of over 11M active developers. On the second tier we have Java (6.9M) and Python (6.8M).

Our data challenges the assumption that developers’ language use is relatively stable over time. Instead, it seems that developers drop and adopt new languages all the time, depending on their needs and on their running projects.

Kotlin is the rising star among programming languages. It moved up from 11th to 8th place in just a year.

Growing interest and adoption in 5 emerging technologies

We saw a significant increase in developers’ involvement and adoption of five technologies in the 6 month period ending Q2 2019. These are DevOps, mini-apps, computer vision, cryptocurrencies, and fog/edge computing. For DevOps in particular, the percentage of developers who are either interested in it, learning about it, or have already adopted it increased from 66% to 70%.

Computer vision, on the other hand, saw a noticeable growth in the number of developers involved in it.  Meanwhile, the share of those developers who are actually adopting it increased only slightly.

Interest in robotics and quantum computing also increased.

However, the share of interested developers that are working on the technology dropped.

ŸInterest and adoption in blockchain applications other than cryptocurrency, conversational platforms/voice search, drones and biometric technologies remains constant.

Streaming games and extending reality

ŸJust 16% of professional and 10% of hobbyist game developers say they are actively working on designing games for streamers to live-stream their gameplay to an audience. Gameplay streaming is mostly associated with brand promotion and revenue generation. Therefore, the difference between professional and hobbyist interest is to be expected.

One in five AR/VR game developers design for gameplay streaming. This might be because they are the most comfortable with different models for their games, on emerging hardware and across new business channels.

Decoding development trends across regions and screens

  • 2 out of 5 app developers in Asia build apps for messaging platforms and/or chatbots.
  • 34% of mobile developers used cross-platform frameworks in the last 12 months (40% of professional mobile developers, 33% of hobbyists and students).
  • Almost one in four mobile developers opt to use React Native.
  • 31% of mobile developers whose primary target is iOS are using React Native. This compares with 21% of those who primarily target Android.

You can read the full State of the Developer Nation report here.

We look forward to decoding development trends in our next report. You can help shape the trends by taking the 18th Developer Economics survey here!