Technology Tales

Online learning

Recently, I shared my thoughts on learning new computing languages by oneself using books, online research and personal practice. As successful as that can be, there remains a place for getting some actual instruction as well. Maybe that is why so many turn to YouTube, where there is a multitude of video channels offering such possibilities without cost. What I have also discovered is that this is complemented by a host of other providers whose services attract a fee, and there will be a few of those mentioned later in this post. Paying for online courses does mean that you can get the benefit of curation and an added assurance of quality in what appears to be a growing market.

The variation in quality can dog the YouTube approach, and it also can be tricky to find something good, even if the platform does suggest new videos based on what you have been watching. Much of what is found there does take the form of webinars from the likes of the Why R? Foundation, Posit or the NHSR Community. These can be useful, and there are shorter videos from such providers as the Association of Computing Machinery or SAS Users. These do help more if you already have some knowledge about the topic area being discussed, so they may not make the best starting points for someone who is starting from scratch.

Of course, working your way through a good book will help, and it is something that I have been known to do, but supplementing this with one or more video courses really adds to the experience and I have done a few of these on LinkedIn. That part of the professional platform came from the acquisition of Lynda.com and the topic areas range from soft skills like time management through to computing skills courses with R, SAS and Python seeing coverage among the data science portfolio. Even O’Reilly has ventured into the area in an expansion from the book publishing activities for which so many of us know the organisation.

The available online instructor community does not stop at the above since there are others like Degreed, Baeldung, Udacity, Programiz, Udemy, Business Science and Datanovia. Some of these tend towards online education provision that feels more like an online university course and those are numerous as well as you will find through Data Science Central or KDNuggets. Both of these earn income from advertising to pay for featured blog posts and newsletters, while the former also organises regular webinars and was my first port of call when I became curious about the world of data science during the autumn of 2017.

My point of approach into the world of online training has been as a freelance information professional needing to keep up to date with a rapidly changing field. The mix of content that is both free of charge and that which attracts a fee is one that can work. Both kinds do complement each other while possessing their unique advantages and disadvantages. The need to continually expand skills and knowledge never goes away, so it is well worth spending some time working what you are after, since you need to be sure that any training always adds to your own knowledge and skill level.

Rethinking photo editing

Photo editing has been something that I have been doing since my first-ever photo scan in 1998 (I believe it was in June of that year but cannot be completely sure nearly twenty years later). Since then, I have been using a variety of tools for the job and wondered how other photos can look better than my own. What cannot be excluded is my preference for being active in the middle of the day when light is at its bluest as well as a penchant for using a higher ISO of 400. In other words, what I do when making photos affects how they look afterwards as much as the weather that I had encountered.

My reason for mentioning the above aspects of photographic craft is that they affect what you can do in photo editing afterwards, even with the benefits of technological advancement. My tastes have changed over time, so the appeal of re-editing old photos fades when you realise that you only are going around in circles and there always are new ones to share, so that may be a better way to improve.

When I started, I was a user of Paint Shop Pro but have gone over to Adobe since then. First, it was Photoshop Elements, but an offer in 2011 lured me into having Lightroom and the full version of Photoshop. Nowadays, I am a Creative Cloud photography plan subscriber so I get to see new developments much sooner than once was the case.

Even though I have had Lightroom for all that time, I never really made full use of it and preferred a Photoshop-based workflow. Lightroom was used to select photos for Photoshop editing, mainly using adjustments for such things as tones, exposure, levels, hue and saturation. Removal of dust spots, resizing and sharpening were other parts of a still minimalist approach.

What changed all this was a day spent pottering about the 2018 Photography Show at the Birmingham NEC during a cold snap in March. That was followed by my checking out the Adobe YouTube Channel afterwards where there were videos of the talks featured every day of the four-day event. Here are some shortcuts if you want to do some catching up yourself: Day 1, Day 2, Day 3, and Day 4. Be warned though that these videos are long in that they feature the whole day and there are enough gaps that you may wish to fast-forward through them. Even so, there is quite a bit of variety of things to see.

Of particular interest were the talks given by the landscape photographer David Noton who sensibly has a philosophy of doing as little to his images as possible. It helps that his starting points are so good that adjusting black and white points with a little tonal adjustment does most of what he needs. Vibrancy, clarity and sharpening adjustments are kept to a minimum while some work with graduated filters evens out exposure differences between skies and landscapes. It helps that all this can be done in Lightroom, so that set me thinking about trying it out for size and the trick of using the backslash (\) key to switch between raw and processed views is a bonus granted by non-destructive editing. Others may have demonstrated the creation of composite imagery, but simplicity is more like my way of working.

Confusingly, we now have the cloud-based Lightroom CC while the previous desktop counterpart is known as Lightroom Classic CC. Though the former may allow for easy dust spot removal among other things, it is the latter that I prefer because the idea of wholesale image library upload does not appeal to me for now and I already have other places for off-site image backup like Google Drive and Dropbox. The mobile app does look interesting since it allows capturing images on a such a device in Adobe’s raw image format DNG. Still, my workflow is set to be more Lightroom-based than it once was and I quite fancy what new technology offers, especially since Adobe is progressing its Sensai artificial intelligence engine. The fact that it has access to many images on its systems due to Lightroom CC and its own stock library (Adobe Stock, formerly Fotolia) must mean that it has plenty of data for training this AI engine.

Outdoors enthuasiasts blogging in the U.K.