Machine learning is designed to understand and build methods that 'learn' to leverage data to improve performance on a set of tasks. Machine learning algorithms are used in a plethora of applications in medicine, email filtering, speech recognition, and more, where it is challenging to develop conventional algorithms to perform tasks.
The course begins with an introduction to machine learning concepts and explains the motivation for machine learning. The course teaches all major concepts about Python including variables, objects, strings, loops, decision-making statements, classes, and a small project to recap. You will learn to use the power of Python to train your machine and make predictions and implement the ML algorithm “Random Forest.” Use NumPy with Python for array handling, Pandas data frames for Excel files, and matplotlib for data visualization. You will learn to use Random Forest with sklearn, Matplotlib for Python plotting, and SciKit-Learn for Random Forest.
Upon completion, you will Implement the structure of forest, impurity, information gain, partitions, leaf nodes, and decision nodes using Python and create a complete structure for Random Forest using Python to build one tree that lets you create an entire forest. You will write an accuracy calculator function and implement Random Forest on any dataset.
All resources are available at: https://github.com/PacktPublishing/Machine-Learning-Random-Forest-with-…-
Use Random Forest with sklearn and Matplotlib for Python plotting
Use SciKit-Learn for Random Forest using the titanic dataset
Learn forest structure, impurity, partition, leaf/decision nodes
Create a complete Random Forest structure from scratch using Python
Build one tree that adds up to create a complete forest
Write accuracy calculator functions and implement them on any dataset
* Learn data preprocessing steps to prepare data for machine learning algorithms
* Master machine learning concepts and implement the essential ML algorithm, Random Forest
This course is for someone who is an absolute beginner and has truly little or even zero ideas of machine learning or wants to learn random forest from zero to hero.