Currently working as Project Consultant in Airbus India. Also worked as Assistant Prof. for CSE branch. Published few research papers in Dat

Sakshi Agarwal

This course is about Classification & Prediction.
Various Algorithms used for Classification are the foundation for Data Mining & Machine learning practical. So it is one of the most important course in terms of application.

GATE (Graduate Aptitude Test in Engineering) 2020 & 2021 complete preparation with best educators. Know about the detailed syllabus, best books, exam pattern and dates, previous year question papers a

GATE - Iconic Pro

English

Classification And Prediction

Miscellaneous

Practice and Strategy

CS & IT

GATE - CSIT, DSAI & Interview Preparation

GATE, ESE and IIT-JAM

Ace the toughest competitive and government exams in India 

Test Preparation

This lesson gives you Introduction about Classification & Predction.
The general appraoch for classification is explained with two step process- Learning step & Classification Step.

Introduction

This lesson tells the Difference between Supervised & Unsupervised Learning and issues regarding Classification & Prediction.

Issues Regarding Classification and Prediction

This lesson gives Introduction about Decision Tree Induction, why is it used, how are decision tree used for classification & basic steps to be followed in decision tree.

Decision Tree Induction

This lesson takes you in depth of Decision Tree induction, Entropy & Information Gain.

Decision Tree: Information Gain

This lesson gives you idea about Attribute Selection measure, overfitting problem of Decision Tree, extracting rules from decision tree & Enhancements to basic decision tree.

Enhancements to Basic Decision Tree

This lesson tells you the relation between Scalibility & Decision Tree Induction.
It gives you idea about new scalable decision tree algorithms.

Decision Tree and Scalibility

You will dive into the second important & generally used classifier BAYESIAN Classifier.
You will learn about the Bayes Theorem & basics of Naive Bayes.

Bayesian Classification

This lesson will make you understand Naive Bayes Classification with example.

Naive Bayesian Classification

This lesson gives you the introduction of Bayesian Belief Networks.

Bayesian Belief Network

This lesson will tell you a lot about Neural Networks, their advantages, disadvantages, when to use & houw to use. It will make you understand the fuctioning of Multi Layer Feed Forward Neural Network.

Backpropagation

This lesson makes you understand Support Vector Machines (SVM) which is one of the important classifier.

Support Vector Machine

This lesson describes K-nn (k-nearest neighbor) classifier. It tells you the difference between Eager learner & Lazy learner

K-nearest neighbor classifier

This lesson will take you to the depth of Fuzzy logic sets & Genetic Algorithms.

Genetic & Fuzzy Set Classification

This lesson helps you to learn the depth of Ensemble Methods with very simple illustrations. Bagging & Boosting methods are also explained here.

Ensemble Methods

This lesson will give you detail about the Classification Model Evaluation.
How the metrics form the base for evaluation performance of classifier.

Model Evaluation & Selection

In this lesson you will learn about how you should divide your dataset into training & testing dataset using HoldOut & Cross Validation Method.

Evaluation of Accuracy

This lesson gives detail about Prediction & the models which are used for prediction.

Prediction

Code HELLOSONU01 | 8+ Years Teaching Exp. in GATE CS IT & GATE DS AI on Unacademy | Mentored 2 Lakh+ Students | Produced Rankers Under 500

Sweta Kumari

This course includes important formulas from every section targeted for GATE exam.

(Hindi) Short Tricks to Crack GATE with Important Formulas

This course is covering cloud Computing subject in only 60 Minutes. Multiple choice questions are also covered to master the topic.

(Hindi) Learn Cloud Computing and IoT in 60 Minutes

This course will cover the entire syllabus of Software Engineering in 1 hr.

(Hindi) Complete Software Engineering in 60 Minutes

Manpreet Singh

This course is about internet technology, services, servers, computing, artificial intelligence and robots.

(Hindi) Internet, Servers, Artificial Intelligence and Computing

I am a student currently in the final year of my study. I am pursuing BTech from Heritage Institute of Technology, Kolkata.

Shubhabrata Ghosh

This is an introductory course on Software Engineering which includes the basic initial stages involved in a software development company. 
This course also deals with the various models which are followed during the development of a software product.

Introduction to Software Engineering

In this course, Sweta Kumari will give You some tips and tricks with perfect Strategy of 6 Months to Crack GATE Exam.

Lessons

17 lessons • 3h 55m

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Introduction

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Issues Regarding Classification and Prediction

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Decision Tree Induction

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Decision Tree: Information Gain

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Enhancements to Basic Decision Tree

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Decision Tree and Scalibility

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Bayesian Classification

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Naive Bayesian Classification

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Bayesian Belief Network

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Backpropagation

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