When I started out as an audio engineer in church my goal was to just serve and be content with that. Then after a while I asked myself why other local churches did not sound as good and why they seemed to only have failing equipment and yet the gospel has to be taught with clarity not distractions. I had a vision where I would be able to train churches the skills they needed to have a better experience. So I put all my effort into learning audio engineering and found mentors in the field who taught me how to become better. I then went ahead to train a local church for a week and the results were amazing. That church could now record their own sermons, music, edit them and share them. I am glad I took that step of faith to learn the skill and now I have been and keep teaching others.

Don’t be afraid to try something new but more importantly don’t be afraid to teach what you have just learnt. You could be the change that someone else is looking for.

The definition of the word consistency as a character trait in a person is to behave the same way or have the same attitude towards people, situations and achieves the same level of productivity.

Everyone is consistent at something whether it is waking up, eating or missing lunch, driving a car, we are all consistent at the way we do certain activities. The great question i would then have for you is, What would you like to continue being consistent in? Is there a new habit you would like to create? Then start being consistent at it.

Choose a time for what you would like to do. Let it be a part of your being. I personally don’t believe in writer’s block. Apparently Writer’s block is a condition, primarily associated with writing, in which an author is unable to produce new work or experiences a creative slowdown.
The reason i don’t believe this is because there’s no one point in time where you have stopped thinking or asking questions or even reasoning. So you can literary write whatever you dreamt about or thought about this morning.

Also you never hear about walking block, eating block because you do these activities consistently that you no longer think of them as activities. So you can do whatever you need to do until it becomes like walking.

Today i’m going to explain a topic that is increasing in interest around the world and how it possibly applies to your career or company either now or in the future.

Machine Learning

Machine learning is a subset of artificial intelligence that focuses on creating applications that learn from a dataset and improve accuracy over time without being programmed to do so.

The way traditional programming works is you write down a set of rules that will give a result depending on the input/question that the user inserts. In other words if i type into my calculator an addition operation like 1 + 1, the calculator has been programmed to work on addition in a specific way and therefore the result will be 2.

Machine learning takes a different approach instead of writing the rules, the machine writes the rules for itself based on the inputs and results it is given. For example if you give the machine pictures of cats with the breed of the cats and pictures of dogs with the breed of the dogs, it should be able to distinguish either cat or dog if it is ever asked to do so. It should figure out for itself what a dog or a cat is. It writes its own set of rules of what dogs look like and how cats look like.

How Machine Learning works

Let’s dive a little deeper into how it works. The goal is to build a machine learning model/application.
There are 4 steps involved when an ML model is being created.

1. Select a dataset to Train

A dataset is usually a large collection of information like patient records or football club statistics. This dataset is what the model will use to solve the problem it’s designed for.
There are labelled datasets which has labels like cat or dog, breed etc. and there’s also unlabelled datasets of which the machine will classify on it’s own.

Preparation of this data is critical because it is what the ML model will use to produce results. So all the data is checked for duplicate values, biases just to make sure the model gives correct information at the end.

After preparation you split the dataset into a training set and a test set. These sets are different because if you train the model on the whole set it will produced biased results. We’re trying to avoid a scenario where the model crams those specific pictures of cats and dogs and then when given a new picture of a dog gives an error because it didn’t recognise the new picture.

Therefore this is the most important step in the process.

2. Choose an algorithm to work on the training set

An algorithm is a set of statistical steps. An algorithm is chosen based on if your dataset is labelled or unlabelled.
There are different kinds of algorithms for the different datasets:

For labelled datasets there’s regression algorithms, Decision Trees and Instance-based algorithms

For unlabelled datasets there’s Clustering algorithms, Association algorithms and Neural Networks.

There is a lot to cover for each of these i’ll expand on them in future blogs

3. Train the algorithm to create the model

This is where the magic happens. You train the algorithm on the training dataset. It is a repetitive process so depending on the size of your dataset it could take minutes, days, weeks and even years. You typically run variables through the algorithm until the algorithm yields a correct results. And this result is the machine learning model.

Side note: The words algorithm and model are used interchangeably especially by the professionals.

4. Using and improving the model

Now we can use the model on the test dataset and hopefully it improves in accuracy over time. So for our example of cats and dogs, the more pictures it takes in, the better it should get at recognising them.

Applications of Machine Learning

I’m pretty sure you’ve seen examples of machine learning but have never noticed them.

Digital Assistants like Siri, Alexa, Google Assistant use machine learning to change text to voice or voice to text all while understanding the instructions you give them.

Recommendation systems like the ones in Netflix, YouTube give you a better experience of the platform because they know what you are interested in and try their best to give you interesting videos that you might like.

Email spam detection is another one. Have you ever realised that those unnecessary emails don’t reach your main inbox. That is because there’s a machine learning model that has been tasked to separate real emails from fake ones.

Conclusion

The 4 steps when to build a machine learning model are selecting a dataset, choosing an algorithm, training the algorithm and improving the algorithm

We have just touched the surface of this topic but i hope you understand now that the world we live in is evolving and getting more efficient because of tools like machine learning and artificial intelligence and it is touching every aspect of life whether it is medicine, sports, astrophysics or the automobile industry.

Always keep learning.

Do you always have new year’s resolutions that by the end of the year never seem to get fulfilled? Do you find yourself asking what happened? Why you didn’t pick the guitar or why you didn’t start working out?

Well in this blog I’ll be explaining a few things that will help you form a habit. In other words deciding to do something and then actually fulfilling the task no matter how big it is and hopefully it becoming a habit for the rest of your life.

The Decision

The decision that you want to take is a part of you, it is a part of your essence. If you love dancing, you don’t need to wonder if you should enter a boxing ring. The decisions you make are a result of you. The way you think and feel.

So making the decision is actually the first step because you know what you want and you really want to do it. This is usually a decision that will affect your life long term.

Break it Down

The second step is to break it down in chunks. I started doing a machine learning course and some of the pre-requisites were knowing a little bit of python programming and some high school mathematics. I didn’t know anything about python programming but I took a course and started doing it. Even then I still had to break down the python course only doing a couple of classes a day.

The last thing you want to do is overload yourself with information you’re not ready for in one day. It becomes too much and what used to be exciting becomes tedious and annoying and that kills the habit even before it begins. So break down the structure of what you want to learn.

Time and Practice

It takes time to build a habit. You have to create time during the day to develop your habit. A consistent time of the day like 5 am is preferably a good time to build on a habit because there’s not that much activity that time of day for most people. Otherwise pick a time of the day and start practicing.

To be clear it’s not a must to practice long hours, some of you may not have that much time. Let me propose something, how about at least 5 MINUTES. I know what you’re thinking but it’s enough time for your brain to learn something. It doesn’t matter whether you are writing a song or playing an instrument, reading an article.

The idea is this daily 5 minute plan compounds over time and as your mind gets used to doing this routine, within 21 days you would have built a long term memory and within 63 days you would have formed a habit.

Conclusion

If you want to develop a habit. Make the choice to do it, break it down into chunks that are easy for your brain to digest then set a time everyday to actually practice, a minimum of 5 minutes.

Remember to do what you love.