This course is completely categorized, and we don’t start from the middle! We actually start from the concept of every term, and then we try to implement it in Python step by step. The structure of the course is as follows:
Chapter1: Introduction and all required installations
Chapter2: Useful Machine Learning libraries (NumPy, Pandas & Matplotlib)
Chapter3: Preprocessing
Chapter4: Machine Learning Types
Chapter5: Supervised Learning: Classification
Chapter6: Supervised Learning: Regression
Chapter7: Unsupervised Learning: Clustering
Chapter8: Model Tuning
Furthermore, you learn how to work with different real datasets and use them for developing your models. All the Python code templates that we write during the course together are available, and you can download them with the resource button of each section.
Remember! That this course is created for you with any background as all the concepts will be explained from the basic! Also, the programming in Python will be explained from the basic coding, and you just need to know the syntax of Python.
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