Learning AI by Writing Code, Not Watching Tutorials
The author shares their journey of transitioning from a tutorial hoarder to a budding AI engineer by writing code from scratch, starting with a simple linear regression model to predict house prices.
Why it matters
This article highlights the importance of moving from passive learning to active coding when it comes to developing practical AI skills, which is a common challenge for many aspiring AI engineers.
Key Points
- 1Stopped watching AI tutorials and started writing code
- 2Implemented a linear regression model without using libraries
- 3Learned the underlying math and concepts through hands-on coding
- 4Went through a 4-step process to build practical AI skills
- 5Emphasized the importance of moving from passive learning to active coding
Details
The author realized that watching AI tutorials alone was not enough to develop practical skills. They decided to delete their tutorial watch history and start writing code from scratch. The article focuses on the first phase of their journey, where they implemented a linear regression model to predict house prices. The author explains the step-by-step process, including data preparation, defining the model's 'brain' (slope and intercept), implementing gradient descent for learning, and testing the model on a new house size. This hands-on approach allowed the author to understand the underlying mathematical concepts and gain a deeper understanding of how AI models work, rather than just memorizing tutorial steps.
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