Abstract: Cancer is one of the leading causes of death worldwide. It is caused by a variety of genetic mutations, which makes every instance of the disease unique. Since chemotherapy can have extremely severe side effects, each patient requires a personalized treatment plan. Finding the dosages that maximize the beneficial effects of the drugs and minimize their adverse side effects is vital. Deep neural networks automate and improve drug selection.

I have been working for many months to understand machine learning. It is the most agonizing experience but on the other hand, is a thrilled one. I don't have any experience related to IT or Advanced Calculus. Indeed, I learn calculus in my previous study in college but sometimes memory can fade if it does not use every day, am I correct? Therefore, I have to study the basics of machine learning.

This tutorial aims to provide an introduction to machine learning and scikit-learn "from the ground up". We will start with core concepts of machine learning, some example uses of machine learning, and how to implement them using scikit-learn. Going in detail through the characteristics of several methods, we will discuss how to pick an algorithm for your application, how to set its parameters, and how to evaluate performance.

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