Data Mining

Data Mining

Rs.8,474.00

18% GST Extra

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SKU: cid_191553 Category:

About the course

We are witnessing an unprecedented growth in the amount of data, starting from protein sequences and structures to biomedical images, sensor readings, and chemical data. In order to render this vast amount of data more useful than just a digital data storage structure, the ability to mine for knowledge inherent in the collection must be supported.

This course will cover the standard algorithms for such data mining techniques. Special emphasis will be given on the recent trends in mining text data, mining graphs, mining Spatio-temporal data, etc.

Course Features

24X7 Access: You can view lectures at your own convenience.

Online lectures: Online lectures with high-quality videos.

Updated Quality content: Content is the latest and gets updated regularly to meet the current industry demands.

Test & Evaluation

1. During the program, the participants will have to take all the assignments given to them for better learning.

2. At the end of the program, a final assessment will be conducted.

Certification

1. All successful participants will be provided with a certificate of completion.

2. Students who do not complete the course / leave it midway will not be awarded any certificate.

Bachelor-level databases, algorithms and statistics courses

Course Content

  • What is Metadata?
  • Introduction
  • Anecdote Part 1
  • Anecdote Part 2
  • Data Errors
  • Data
  • Data Preprocessing
  • Dimensionality Reduction
  • Singular Value Decomposition
  • Principal Component Analysis
  • Numerosity Reduction
  • Data Summarization
  • Feature Selection
  • Relief Algo
  • Discretization
  • Entropy
  • Chi-Square
  • Chi Merge
  • Intuitive
  • Warehouse
  • OLAP
  • Association
  • Apriori
  • FP-Tree
  • Arm Other
  • Lift
  • Classification
  • Classification Errors
  • Error Example
  • Decision Tree
  • Measures
  • Random Forest
  • Rule-Based Classifier
  • Rule Quality
  • NB Theory
  • NB Example
  • What are Bayesian Networks?
  • SVM Basics
  • SVM Slack
  • SVM Non-Linear
  • SVM Multi-Class
  • What is perceptron?
  • Artificial Neural Network
  • Artificial Neural Network Training
  • Artificial Neural Network Discussion
  • Deep Neural Network
  • What is the Lazy Learners Method
  • What is the class imbalance?
  • What is Ensemble?
  • What is regression?
  • Clustering
  • Subspace Clustering
  • Cluster Evaluation
  • K-means
  • K-medoids
  • Hierarchical
  • Cluster Distances
  • Birch
  • Cure
  • Rock
  • Chameleon
  • DB Scan
  • Optics
  • Denclue
  • Sting
  • Clique
  • Model Clustering
  • What Anomaly in Data Mining?
  • Statistical Framework
  • Statistical Distributions
  • Distance Density
  • Clustering Outlier
  • High Dimensional

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