Structure For Machine Learning

Skills

Numpy, Pandas, Data visualisation, Data acquisition,
 Data Cleaning, sklearn, Regression, Classification,
 Model Tuning, SVM, XGboost

Perks

5 Projects
Chance to get your Article published 
Certificates
Portfolio Making and hosting
Internship Chance.

Structure of Modules

Module 1


Revisiting Python Libraries

What is Data Science

Data acquisition
(Numpy, Pandas)
 
Data visualisation (Matplotlib, Seaborn)
 
Data cleaning

1st Project Submission & Leader board Updated.

Module 2


Introduction to ML

Types of learning (Supervised vs Unsupervised)
 
Regression vs Classification
 
Performance measure (accuracy,confusion matrix, F1-score)

2nd Project Submission & Leader board Updated.

Module 3


 Linear regression

   Project (house pricing Estimation)
 
Overfitting and underfitting
 
Bias variance trade-off

3rd Project Submission & Leaderboard Updated.

Module 4


Logistic Regression

   Project (Ad click prediction)
 
SVM
    
Project(iris flower classification)

Boosting

4th Project Submission & Leader board Updated.

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