# Hands-on Machine Learning

- [I. The Fundamentals - ML](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml.md)
- [1. The ML Landscape](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/ml-landscape.md): I tried to summarize the important details of the Machine Learning landscape given in the book as well as adding more details to explain some concepts better. This chapter is extremely important.
- [2. End-to-End ML Project](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/ml-project.md): I summarized the important steps and libraries used in the ML project rather than focusing on the codes. The notebook for this chapter is available at github.com/ageron/handson-ml2
- [3. Classification](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/classification.md)
- [4. Training Models](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/train-models.md)
- [5. SVM](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/svm.md)
- [6. Decision Trees](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/decision-trees.md)
- [7. Ensemble Learning & Random Forests](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/ensemble-and-random-forests.md)
- [8. Dimension Reduction](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/dimension-reduction.md)
- [9. Unsupervised Learning](https://salihkilicli.gitbook.io/notes/books/handsonml2/fund-ml/unsupervised-learning.md)
- [II. Neural Networks  -  DL](https://salihkilicli.gitbook.io/notes/books/handsonml2/nn-dl.md)


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