What you'll learn

Build regressor, classifier and clusters for real world application using online project working environment and that too without ing any software.

Make prediction using linear regression and optimization model coefficents using gradient descent algorithm

To build a logistic regression classifier to predict customer purchased decision

To classify mall customers based on k means clustering for market basket analysis. Use of ELBOW method to detect optimal k value

To identifying the gender of a voice using SVM classifier

Data visualization with seaborn and matplotlib library

Model perfromance evalution using metrics like MSE, R-square error, confusion matrix, precision, recall, f1-score

K-fold cross validation method

Requirements

Bner python is required; but that is also optional.

Google colab -free cloud based Jupyter notebook environment

Description

This project based course consists of video lectures with coding on cloud based Jupyter notebooks.

It guides you to set up an easy and interactive project working environment without ing any software.

It's a bunch of 5 projects based on machine learning algorithms covering all details of implementation in python.

You can go through side by side video lectures to implement step wise projects inthe given worksheet as per your pace.

Finally you can whole project code.

Final project solution sheets are also provided.

Who this course is for:

Bner python developers curious about machine learning algorithms

Anyone who want to upgrade skill in machine learning domain.

Job aspirants who want to start career as machine learning eeer, data scientist etc.

Technologists who is curious to know about machine learning models

Any students who is interested in AI, ML and IOT domains.



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