Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: aac, 44100 Hz
Language: English | VTT | Size: 4.46 GB | Duration: 9h 14m

The course covers Machine Learning in exhaustive way.


What you’ll learn

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

Requirements

working knowledge of python

Description

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

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

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