This is an AssemblyAI course where you don’t rely on libraries like Pytorch or Tensorflow to implement machine learning algorithms, but implement them yourself from scratch using only Python and NumPy.
Algorithms to be implemented:
- K-Nearest Neighbors
- Linear Regression
- Logistic Regression
- Decision Trees
- Random Forest
- Naive Bayes
- K Means
You need a basic understanding of Python, object-oriented programming, and NumPy basics to take this hands-on course.
Overall, this is a very interesting course that offers a fresh perspective on machine learning from the inside. All accompanying code can be found in the course’s Github repository.
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