Machine Learning Study guides, Class notes & Summaries

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The document gives you a detailed explanation to how a linear regression can be performed on polynomial features. It dives inside the mathematics and linear algebra involved in the process.

The document contains all the necessary algorithms, Machine Learning and statistics techniques. The document also contains approach for data pre-processing and applying those algorithms to the data available.

What is supervised learning? A type of machine learning which is used when we want to predict a certain output from a given input and have examples of input/out pairs. The training set we feed into the algorithm includes the desired solutions (labels). labelled data: each instance comes with the expected output What are the two types of supervised machine learning? (1) classification - binary classification: 2 classes - multiclass classification: classification between more than 2 ...

Machine Learning Machine learning is defined as an automated process that extracts patterns from data. Supervised Machine Learning To build the models used in predictive data analytics applications, we used supervised machine learning. Supervised machine learning techniques automatically learn a model of the relationship between a set of descriptive features and a target feature based on a set of historical examples, or instances. We can use this model to make predictions for new instan...

Tells about the concepts of the k-Nearest Neighbors Algorithm, Similarity

this a not on gradient descent and linear regression using it