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GitHub - AntonioErdeljac/Google-Machine-Learning-Course-Notes: Notes taken from...
source link: https://github.com/AntonioErdeljac/Google-Machine-Learning-Course-Notes
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README.md
Google Machine Learning Course Notes
Wiki
- Framing
- In this section we learn the basics of Machine Learning Terminology
- Descending into Machine Learning
- In this section we work with linear regression, learn about MSE, loss caculation and the basics of how training a model works
- Reducing Loss
- In this section we explore loss reduction methods by explaining gradient descent, batches, iterative learning and other effective learning methods
- First Steps With Tensorflow
- In this section we learn the basics of TensorFlow and Pandas. Through practices linked we develop our own linear regression code
- Generalization
- In this article we discuss the problem of overfitting, learn the difference between a good and a bad model, learn about subsets used in model training & generalization
- Training and test sets
- In this section we learn about data splitting, dangers of training on test data & test data characteristics
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