Dimakatso Makgatho
TechStack

TechStack

What is Machine Learning?

What is Machine Learning?

The Machine Learning Series

So I recently embarked on a journey to equip my skillset with Machine Learning and along with that, I decided to write a blog while actively learning it. And guess what? This is my First Blog post, so excuse me if you get a bit bored now and thenπŸ˜†πŸ˜†πŸ˜†. Now, let's jump right:

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What is Machine Learning? You are probably thinking The Matrix or maybe The Terminator? Well, you are not too far off, as Machine Learning is a subset of artificial intelligence (AI) that enables computers to solve problems by using real-world data. This allows computers to continuously learn and improve without explicitly being programmed to do so.

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While traditionally, a human element is required to solve a problem, with Machine Learning we move away from this approach. A problem solver (human element) is usually required to analyse and compute a solution for the problem before programming it. Now, with Machine Learning, the problem solver uses the general idea of what the problem is and how to solve it as a flexible component called a model, and uses an algorithm to adjust the model to real-world data. Machine Learning being an intersection of statistics, computer science, and applied mathematics automates the statistical reasoning and pattern-matching traditionally done by the problem solver. Remember, that the better the training data, the better the model will be.

Machine Learning has three learning subsets. What are they you ask?

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Supervised learning: Every sample from the dataset has a corresponding label/output value associated with it. Thus, the algorithm learns to predict the labels/output values. Unsupervised learning: The training data has no labels for the training data. The algorithm tries to learn the underlying patterns or distributions that govern the data. Reinforcement learning: An algorithm figures out which actions to take in a situation to gain the maximum reward (a numerical value) to achieve the specific goal.

Seems like you've made it to the end of this boring blog😁😁😁. Well, I hope you enjoyed it and you'll be following my machine learning journey. To keep up with my journey follow me on Hashnode and Twitter - I'll try to keep my posts short and to the point, also feel free to comment tips and notes for me. But for now, pick a pill (The Matrix reference - for all you young ones that might not know)!

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