Struggles in Learning ML
Do you spend hours of your day in front of large textbooks to learn mathematical concepts of machine learning such as linear algebra, calculus, or statistics? Learning Machine learning concept is highly challenging and time-consuming. But there is no need to worry. I will explain an easy solution to overcome the fear of learning large, tougher concepts of machine learning in less than an hour. Get ready to raise your ML skills.
Discovering an Easy and Relevant Path
I spent a long time browsing the web to figure out the easiest way to enhance my machine learning skills. I found lots of articles and YouTube videos, but most of them were too technical and challenging to understand without a solid foundation in ML-related mathematics.
I was looking for hands-on projects, so I could experiment and learn theoretical concepts simultaneously. Finally, I decided to build a spam-detection machine learning model, which doesn't require much deeper ML knowledge and serves as a real-world problem for learning each step in training a model in machine learning. Our model will predict whether an email is spam or not.
During this journey, we uncover the secrets behind each stage of machine learning model training and testing, including visualizing result using a confusion matrix.
How to Train a Simple ML Model
Training a machine learning model involves multiple steps, such as
- collecting the appropriate data
- preprocessing or cleaning the data
- choosing the best algorithm for our model
- evaluating and visualizing the results.
After completing the fourth step, we will get a solid idea of how machine learning models are trained to predict information.
Collecting Data for our ML Model
Continue reading the full article at https://journal.hexmos.com/spam-detection-ml/
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