Machine Learning made Easy : Unsupervised & Supervised ML

Machine Learning made Easy : Unsupervised & Supervised ML

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Machine Learning made Easy : Unsupervised & Supervised ML Hands-on Machine Learning  Machine Learning (ML) is a subfield of AI that uses statistical mathematical ... are Supervised, Unsupervised, and Reinforcement Learning.

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What you'll learn

• Applications of Machine Learning to various data, Unsupervised Learning, Supervised Learning

Requirements

• working knowledge of python

Description

The course covers Machine Learning in exhaustive way. The presentations and hands-on practical are made such that it's made easy. The knowledge gained through this tutorial series can be applied to various real world scenarios.

UnSupervised Learning and Supervised Learning are dealt in-detail with lots of bonus topics.

The course contents are given below:

• Introduction to Machine Learning
• Introductions to Deep Learning
• Installations
• Unsupervised Learning
• Clustering, Association
• Agglomerative, Hands-on
• DBSCAN, Hands-on
• Mean Shift, Hands-on
• K Means, Hands-on
• Association Rules, Hands-on
• (PCA: Principal Component Analysis)
• Supervised Learning
• Regression, Classification
• Train Test Split, Hands-on
• k Nearest Neighbors, Hands-on
• kNN Algo Implementation
• Support Vector Machine (SVM), Hands-on
• Support Vector Regression (SVR), Hands-on
• SVM (non linear svm params), Hands-on
• SVM kernel trick, Hands-on
• SVM mathematics
• Linear Regression, Hands-on
• Gradient Descent overview
• One Hot Encoding (Dummy vars)
• One Hot Encoding with Linear Regr, Hands-on
• Info about Datasets

Who this course is for:

• python programmers, C/C++ programmers, working of scripting (like javascript), fresh developers and intermediate level programmers who want to learn Machine Learning