# Prob & Stats Gap

When it comes to the mathematical underpinnings for Deep Learning, I’m *extremely passionate*. In fact, my perspective can be summarized succinctly:

Deep Learning – Deep Math = Deep Gap.

In reflecting upon my own mathematical credentials for Deep Learning, when it came to probability and statistics, I previously stated:

Through a number of courses in Time Series Analysis (TSA), my background affords me an appreciation for prob & stats. In other words, I have enough context to

appreciatethis need, and through use of quality, targeted resources (e.g., Goodfellow et al.’s textbook), I can close out the gaps sufficiently – in my case, for example, Bayes’ Rule and information theory.

# Teaching to Learn

Although I can certainly leverage quality, targeted resources, I wanted to share here a complementary approach. One reason for doing this is that resources such as Goodfellow et al.’s textbook may not be readily accessible to everyone – in other words, some homework is required *before* some of us are ready to crack open this excellent resource, and make sense of the prob & stats summary provided there.

So, in the spirit of progressing towards being able to leverage appropriate references such as Goodfellow et al.’s textbook, please allow me to share here a much-more pragmatic suggestion:

Tutora few high school students in prob & stats tolearnprob & stats.

Just in case the basic premise of this suggestion *isn’t* evident, it is: By *committing* to **teaching** prob & stats, you *must* be able to **understand** prob & stats. And as an added bonus, this commitment of tutoring each of a few students (say) once a week, establishes and reinforces a **habit** – a habit that is quite likely, in this case, to *ensure* you stick with your objective to broaden and deepen your knowledge/skills when it comes to probability and statistics.

As an added bonus, this is a **service** for which you could charge a fee – full rate for tutoring math at the high-school level to gratis, depending upon the **value** you’ll be able to offer your students … of course, a rate you could adjust over time, as your expertise with prob & stats develops.

# Agile Sprints

Over recent years, I’ve found it *particularly* useful to frame initiatives such as this one in the form of **Agile Sprints** – an approach I’ve adopted and adapted from the pioneering efforts of J D Meier. To try this for yourself, I suggest the following two-step procedure:

- Review JD’s blog post on sprints – there’s also an earlier post of his that is both useful and relevant.
- Apply the annotated template I’ve prepared here to a sprint of your choosing. Because the sample template I’ve shared is specific to the prob & stats example I’ve been focused on in this post, I’ve also included a blank version of the sprint template here.

# 4DX*it*

Before you go, there’s one final point I’d like to draw your attention to – and that’s lead and lag measures. Whereas **lag** measures focus on your (wildly) important goal (WIG), **lead** measures emphasize those *behaviors* that’ll get you there. To draw from the example I shared for addressing a math gap in prob & stats, the lag measure is:

MUST have enhanced my knowledge/skills in the area of prob & stats such that I am better prepared to review Deep Learning staples such as Goodfellow et al.’s textbook

In contrast, examples of lead measures are each of the following:

SHOULD have sought tutoring positions with local and/or online services

COULD have acquired the textbook relevant for high-school level prob & stats

With appropriately crafted lead measures then, the likelihood that your WIG will be achieved is **significantly*** enhanced*. Kudos to Cal Newport for emphasizing the importance of acting on lead measures in his Deep Work book. For

*all four*disciplines of execution, you can have a closer look at Newport’s book, or go to the 4DX source – the book or by simply Googling for resources on “the 4 disciplines of execution”.

Of course, the approach described here can be applied to much more than a gap in your knowledge/skills of prob & stats. And as I continue the process of self-curating my Data Science Portfolio, I expect to unearth additional challenges and opportunities – challenges and opportunities that can be well approached through 4DX’d Agile Sprints.