6 new eBooks for programmers to watch out for in March

6 min read

The biggest challenge for anyone working in tech is that you need multiple sets of eyes. Yes, you need to commit to regular, almost continuous learning, but you also need to look forward to what’s coming next.

From slowly emerging trends that might not even come to fruition (we’re looking at you DataOps), to version updates and product releases, for tech professionals the horizon always looms and shapes the present.

But it’s not just about the big trends or releases that get coverage – it’s also about planning your next (career) move, or even your next mini-project. That could be learning a new language (not necessarily new, but one you haven’t yet got round to learning), trying a new paradigm, exploring a new library, or getting to grips with cloud native approaches to software development.

This sort of learning is easy to overlook but it is one that’s vital to any developers’ development. While the Packt library has a wealth of content for you to dig your proverbial claws into, if you’re looking forward, Packt has got some new titles available in pre-order that could help you plan your learning for the months to come.

We’ve put together a list of some of our own top picks of our pre-order titles available this month, due to be released late February or March.

Take a look and take some time to consider your next learning journey…

Hands-on deep learning with PyTorch

TensorFlow might have set the pace when it comes to artificial intelligence, but PyTorch is giving it a run for its money.

Hands On Deep Learning with PyTorch cover

It’s impossible to describe one as ‘better’ than the other – ultimately they both have valid use cases, and can both help you do some pretty impressive things with data.

Read next: Can a production ready Pytorch 1.0 give TensorFlow a tough time?

The key difference is really in the level of abstraction and the learning curve – TensorFlow is more like a library, which gives you more control, but also makes things a little more difficult.

PyTorch, then, is a great place to start if you already know some Python and want to try your hand at deep learning. Or, if you have already worked with TensorFlow and simply want to explore new options, PyTorch is the obvious next step.

Order Hands On Deep learning with PyTorch here.

Hands-on DevOps for Architects

Distributed systems have made the software architect role incredibly valuable. This person is not only responsible for deciding what should be developed and deployed, but also the means through which it should be done and maintained. But it’s also made the question of architecture relevant to just about everyone that builds and manages software.

Hands On DevOps for Architects cover

That’s why Hands on DevOps for Architects is such an important book for 2019. It isn’t just for those who typically describe themselves as software architects – it’s for anyone interested in infrastructure, and how things are put together, and be made to be more reliable, scalable and secure.

With site reliability engineering finding increasing usage outside of Silicon Valley, this book could be an important piece in the next step in your career.

Order Hands-on DevOps for Architects here.

Hands-on Full stack development with Go

Go has been cursed with a hell of a lot of hype. This is a shame – it means it’s easy to dismiss as a fad or fashion that will quickly disappear.

Hands On Full Stack Development with Go cover

In truth, Go’s popularity is only going to grow as more people experience, its speed and flexibility. Indeed, in today’s full-stack, cloud native world, Go is only going to go from strength to strength.

In Hands-on Full Stack Development with Go you’ll not only get to grips with the fundamentals of Go, you’ll also learn how to build a complete full stack application built on microservices, using tools such as Gin and ReactJS.

Order Hands-on Full Stack Development with Go here.

C++ Fundamentals

C++ is a language that often gets a bad rap. You don’t have to search the internet that deeply to find someone telling you that there’s no point learning C++ right now. And while it’s true that C++ might not be as eye-catching as languages like, say, Go or Rust, it’s nevertheless still a language that still plays a very important role in the software engineering landscape. If you want to build performance intensive apps for desktop C++ is likely going to be your go-to language.

Read next: Will Rust replace C++?

C++ Fundamentals cover

One of the sticks that’s often used to beat C++ is that it’s a fairly complex language to learn. But rather than being a reason not to learn it, if anything the challenge it presents to even relatively experienced developers is one well worth taking on. At a time when many aspects of software development seem to be getting easier, as new layers of abstraction remove problems we previously might have had to contend with, C++ bucks that trend, forcing you to take a very different approach. And although this approach might not be one many developers want to face, if you want to strengthen your skillset, C++ could certainly be a valuable language to learn.

The stats don’t lie – C++ is placed 4th on the TIOBE index (as of February 2019), beating JavaScript, and commands a considerably high salary – indeed.com data from 2018 suggests that C++ was the second highest earning programming language in the U.S., after Python, with a salary of $115K.

If you want to give C++ a serious go, then C++ Fundamentals could be a great place to begin.

Order C++ Fundamentals here.

Data Wrangling with Python & Data Visualization with Python

Finally, we’re grouping two books together – Data Wrangling with Python and Data Visualization with Python. This is because they both help you to really dig deep into Python’s power, and better understand how it has grown to become the definitive language of data.

Data Wrangling with Python cover

Of course, R might have something to say about this – but it’s a fact the over the last 12-18 months Python has really grown in popularity in a way that R has been unable to match.

So, if you’re new to any aspect of the data science and analysis pipeline, or you’ve used R and you’re now looking for a faster, more flexible alternative, both titles could offer you the insight and guidance you need.

Order Data Wrangling with Python here.

Order Data Visualization with Python here.

Richard Gall
Co-editor of the Packt Hub. Interested in politics, tech culture, and how software and business are changing each other.

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