Fundamentals of machine learning to get you started in the field
What you will learn
Basic understanding of Machine Learning.
What machine learning is.
Why we use machine learning.
What are the types of the machine learning systems.
What are the challenges in machine learning.
Underfitting/Overfitting.
And a lot more.
Description
Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to “self-learn” from training data and improve over time, without being explicitly programmed. Machine learning algorithms are able to detect patterns in data and learn from them, in order to make their own predictions. In short, machine learning algorithms and models learn through experience.
In traditional programming, a computer engineer writes a series of directions that instruct a computer how to transform input data into a desired output.
Machine learning, on the other hand, is an automated process that enables machines to solve problems with little or no human input, and take actions based on past observations.
In this course we are going to talk about the basics of the machine learning which will provide a strong foundation to the students who want to make a career in the field of data sciences and machine learning, we will go through each of the basic important thing that a beginner needs to know to get started with machine learning. We will be talking about what is the machine learning and why exactly we need to use the machine learning, then we will discuss the types of the machine learning system where we will be going in detail about all type and classification of the machine learning system. Then we will talk about the main problems that the data scientist face when they perform machine learning task or making a machine learning algorithm.
This course is introductory, do not expect high level coding and programming, this course is just to build a foundation on which a strong building shall stand.
Content