“Mindfulness” or just “it’s easy to believe what you want to hear”? ;)

I’m a fan of @myfitnesspall and the Blog they publish about health, nutrition, lifestyle, fitness, etc.  Today I came across a really interesting article on ‘mindfulness’ called “The One Trick to Feeling No Guilt When You Skip the Gym” and it made me think of a quote from Barry Fife in the move Strictly Ballroom … “Yeah, it’s easy to believe what you want to hear!” said to Les, when Les was saying he thought Doug wanted Shirley to dance with him in the Pan Pacifics.

Mindfulness, applied to your health, nutrition, lifestyle, fitness is sometimes making a conscious decision to do something you would otherwise deny yourself because it would be “bad for you”.

It sounds great, avoid the cognitive dissonance from a stressful decision by being mindful that you are choosing to do this and being comfortable with your choice.

Cool 😎 I just have to work harder on the “self belief” when I make a decision I just *know* will be bad for me 😜 😂

But seriously, it is a thought-provoking blog and one that’s well worth reading

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Data Science: New data profiling package to try (Python)

This won’t be news to people who already know how to do data science work in Python but I came across a ‘new’ package the other day in a presentation at work – pandas-profilings – see https://github.com/pandas-profiling/pandas-profiling

Learning data science, I have been learning the fundamentals a.k.a how to do stuff from scratch. I think that’s very useful but it does take time. It’s always a pleasure to then find a way of doing all the stuff you have just learnt in one easy step. That’s what pandas-profiling tries to do.

Pandas by itself is a wonderful collection of really useful data wrangling/ profiling tools but so far I’m not missing having to do things one at a time.

This package is worth having in your tool kit, especially when you are working with unfamiliar data. It takes the ‘grind’ out of getting to know the data before moving on to finding insights 🙂

Machine Learning: starting my magical mystery tour

For the past few months, I have been on a sort of Magical Mystery Tour learning about ‘machine learning’, data science and AI. I still can’t tell you the exact differences between them all but it does not matter to me, I just prefer to let art wash over me 😜

My journey began late last year when I set up an interest, nay, ‘working group’ with a few colleagues at work. It started small and now we have over 60 people in the working group. There’s not much ‘working’ going on 😂 but we have fun trying

Right now, the keen people in the group are all learning some variety of data science/ machine learning. We have 4 learning groups:

Azure machine learning

AWS machine learning

Python, and

R

The Python and Azure groups are the most popular so far, Python already has a big fan base at work (as a more generalised programming and scripting language) and Microsoft’s Azure machine learning tools are very approachable, I think Microsoft have done a really good job! 👍😀

I am ‘leading’ the R machine learning learning group, its a bit like the ‘blind leading the blind’ as I didn’t know any R before I started and now I’m half way through a very good course on a site called datacamp.com #DataCamp The course I am doing is called “Data science with R”.

I am also doing some other courses in parallel and while I am enjoying it all I find that I am spreading myself a bit thin and recently I have had to pause some courses to focus on fewer at a time. There just aren’t enough hours in the day 🤓

So far, I am finding that I seem to have an affinity for ‘data wrangling’ and my background in data stuff gives me a good base to work from. The hard part for me is knowing what algorithms to use when it comes to making sense of the data, I just don’t have the maths/stats background for this but I am hoping it is something I can grow into along the way. The most interesting part is really learning the ‘work flow’ involved and the ‘mindset’ around setting goals, trying out ideas, failing, learning and trying again.

Another great resource that I have been using is edX.org #edX.org. My journey started there with a course called “Data Science: R basics” and I have since done quite a few other courses, including “Introduction to AI” … I am current contemplating doing a full course with one of the university providers on edX.org HarverdX is one of the providers and looks to have a really good one but I am still undecided as it would be a huge time commitment over and above what I’m doing now

For now I am happy to do ‘bespoke’ modules on datacamp and edX.org and develop my overall skills and experience. One thing I really like about datacamp is access to supporting resources like their ‘data science cheat sheets’ – A3 size posters/ infographics that give you a nice summary of a topic to put on the wall or in a folder near your computer.

That’s about all for my opening blog on my machine learning/ data science magical mystery tour… more to follow as I continue my journey! 😎

Forgive me WordPress for I have sinned^h^h^h^h^h^h not blogged

Wow, its been quite a few months since I last blogged, where did the time go?!??

Over the past few months, I have been on a ‘machine learning’ magical mystery tour, and its still going 😂

I think I will blog about some of my experiences, starting now, while I sit here with my coffee and 2nd breakfast, typing away on my iPad Pro…

Write Better JavaScript With Webpack | Forestry.io

This post will explore why Webpack is the right choice for bundling your JavaScript application. If you’ve never used a build tool for your frontend assets, Webpack is a great place to start. /
— Read on forestry.io/blog/write-better-javascript-with-webpack/

Read and learn 😀

Azure: Machine Learning

Just a short post to promote a really nice ‘cheat sheet’ for Machine Learning algorithms from Microsoft Azure.

Other links on the same page include:

• An infographic on Machine Learning basics
• Tips on how to choose ML algorithms ,  and
• If you are an Azure ML user/ student – the A-Z of ML modules available in Azure.

Python: Machine learning with Pandas

This one’s relatively old, 2015, but gives a good insight into one of the now (hot) Python based machine learning frameworks, Pandas.