We all have these things. Things that we ‘want’ to do, but we don’t have time so we will do that later.
Things like
starting a blog starting a youtube channel learning that new skill meditating I have found that one simple truth holds for all of thes kinds of activities.
Today marks the first day of what may be my last ever trip with my family.
I’ve been very lucky over the years to go on trips with my family to places all over Australia. We’ve been to many places and experienced many good times together.
On completing my university studies
So my time in university is over. Unless I return to do a masters degree, I won’t be back in a university for some time.
I have now completed 5 years at university, graduating with a Bachelor of Mathematical and Computer Sciences with a Bachelor of Finance.
The following is my solution a practice exam paper with the following brief
An important part of a data scientist’s toolbox is the ability to clean data. To assess your ability to do this, you are required to explain the key goals of data cleaning and how it is applied in tidymodels.
The infinite field of creativity.
Three days ago, I set myself a challenge. To create one blog post for every day until the end of January. This would make 10 weeks of blog posting, 70 posts in total.
When elite sportspeople win their events, you can see the emotion in their eyes.
I encourage you to watch the short video below.
This video is an incredible example of someone that has given everything they have to reach their goal.
What is Kubernetes? Post about the Seth Godin podcast on Tom Bilyeu? Routines The power of walking as cardio nature of innovation Efficiency vs stability FIRE the best mindset how does afterpay make money? University GPA (does it matter?) Japanese housing crash placebo effect
So it begins.
I’ve really wanted to step out of my comfort zone recently. In particular, I’ve wanted to start creating content vs just consuming.
I see this challenge as my first step towards making this a habit.
So you’ve decided on your model for your dataset. How can we now go and see how good that model is?
Maybe we can find the error rate for our training set, or the error from our test set.