Machine learning is eating up the world and to stay ahead of the game you need to master this field of complex thinking!!
work on a data-driven machine learning algorithm - K Nearest Neighbor (KNN). KNN works on the principle of majority wins and similarity matters.
A Support Vector Machine (SVM) is powerful and flexible Machine Learning algorithm. It can work on dataset of small or medium size (say, 100 to 10K datapoints). Many major ML tasks - Regression, Classification and outlier detection can be achieved using SVMs.
In this post we will work our way through a regression problem but now with a dataset that is not in a simple linear form. That is, the next value in the data is not linearly dependent on the previous value. Using some intuitive ideas we will see how manipulating datasets is a key ingredient of the Machine Learning recipes. Alongside we will also limit, regulate and monitor the performance of our model.
We will build a simple model that will be able to take some details about a breast cancer and will inform us whether the cancer is Malignant (M) and Benign (B).
Often the concepts are taught but not implemented. It is not only crucial for learning but also a vital player in development of insights that gives developer ways to fine tune model based on the task at hand. Let's build our intuition about Linear Regression.
To be aware of this society where we have AI eating up the industry we need to know what really goes inside this mystery box. Today we will be opening up the box and will try to expand our knowledge one post at a time.