Foundation Course – Machine Learning
About Course
In the real world, we are surrounded by humans who can learn everything from their experiences with their learning capability, and we have computers or machines which work on our instructions. But can a machine also learn from experiences or past data like a human does? So here comes the role of Machine Learning.
A Machine Learning system learns from historical data, builds the prediction models, and whenever it receives new data, predicts the output for it. The accuracy of predicted output depends upon the amount of data, as the huge amount of data helps to build a better model which predicts the output more accurately.
Suppose we have a complex problem, where we need to perform some predictions, so instead of writing a code for it, we just need to feed the data to generic algorithms, and with the help of these algorithms, machine builds the logic as per the data and predict the output. Machine learning has changed our way of thinking about the problem. The below block diagram explains the working of Machine Learning algorithm
- Machine learning uses data to detect various patterns in a given dataset.
- It can learn from past data and improve automatically.
- It is a data-driven technology.
- Machine learning is much similar to data mining as it also deals with the huge amount of the data.
Course Content
PreAssessment
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What is Python?
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Quiz
Module 1 – Foundations of Statistics and Mathematics for Data Science Data Representations
Module 1 – Understanding the spread of the data
Module 2 – Modules for Machine Learning
Module 3 – Introduction Sclera to Machine Learning
Module 4 – Regression and Classification Fundamentals of simple Linear Regression (OLS)
Module 4 – Multiple Linear Regression
Module 5 – Clustering and Association Clustering
Module 6 (Practical)
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