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Course10610584860 lectures

Statistical Foundation for Big Data Analysis

Prof. Arindam Banerjee · IIT Kharagpur

Start with lecture 1 At NPTEL

Lectures

Week 1

  1. Lecture 1 : Big Data : Definition, Examples and Challenges Video
  2. Lecture 2 : Big Data Analysis vs Big Data Processing : Role of Dimensional Statistics. Video
  3. Lecture 3 : Statistical Framework 1 Video
  4. Lecture 4 : Statistical Framework 2 Video
  5. Lecture 5 : Statistical Framework 3 Video

Week 2

  1. Lecture 06 : Point Estimation: Unbiased Estimation Video
  2. Lecture 07 : Point Estimation: Likelihood 1 Video
  3. Lecture 08 : Point Estimation: Likelihood 2 Video
  4. Lecture 09 : Method of Moments Video
  5. Lecture 10 : Point Estimation: Asymptotics Video

Week 3

  1. Lecture 11 :Interval Estimation 1 Video
  2. Lecture 12 : Interval Estimation 2 Video
  3. Lecture 13 : Basics of Hypothesis Testing-I Video
  4. Lecture 14 : Basics of Hypothesis Testing-II Video
  5. Lecture 15 : Basics of Hypothesis Testing-lll Video

Week 4

  1. Lecture 16 :Bias Variance and Mean Squared Errors Video
  2. Lecture 17 :Bias Variance and Mean Squared Errors Video
  3. Lecture 18 :Bias Variance and Mean Squared Errors Video
  4. Lecture 19 :Bias Variance and Mean Squared Errors Video
  5. Lecture 20 : Bias Variance and Mean Squared Errors Video

Week 5

  1. Lecture 21 : Bias Variance Decomposition Video
  2. Lecture 22 : Cross Validation and Bias Variance Tradeoff Video
  3. Lecture 23 : Methods of Cross Validation Video
  4. Lecture 24 : Regression vs Classification Video
  5. Lecture 25 : Inference on Logistic Regression Video

Week 6

  1. Lecture 26 : Regression: Linear Regression Video
  2. Lecture 27 : Regression: Linear Regression 2 Video
  3. Lecture 28 : Regression: Multiple Linear Regression 1 Video
  4. Lecture 29 : Regression: Multiple Linear Regression 2 Video
  5. Lecture 30 : Regression: Multiple Linear Regression 3 Video

Week 7

  1. Lecture 31 : Generalities of Multivariate Distribution Video
  2. Lecture 32 : Bivariate Normal Distribution Video
  3. Lecture 33 : Multivariate Normal Distribution 1 Video
  4. Lecture 34 : Multivariate Normal Distribution 2 Video
  5. Lecture 35 : Multivariate Normal Distribution 3 Video

Week 8

  1. Lecture 36 : Supervised Learning vs Unsupervised Learning Video
  2. Lecture 37 : Heirarchical Clustering Video
  3. Lecture 38 : K-means clustering Video
  4. Lecture 39 : Curse of Dimensionality Video
  5. Lecture 40 : Behaviour of Volume in High Dimension Video

Week 9

  1. Lecture 41 : Introduction to Principal Component Analysis Video
  2. Lecture 42 : Eigenvalues and Eigenvectors Video
  3. Lecture 43 : Mathematical Formulation of Principal Component Analysis Video
  4. Lecture 44 : Mathematical Foundation of Principal Component Analysis Video
  5. Lecture 45 : Population Principal Component Analysis for Normal Distribution Video

Week 10

  1. Lecture 46 : Population vs Sample Principal Component Analysis Video
  2. Lecture 47 : Mathematical Formulation of Sample PCA Video
  3. Lecture 48 : Sample PCA for Covariance matrix and Correlation Matrix Video
  4. Lecture 49 : Examples of Sample PCA Video
  5. Lecture 50 : Inference on Principal Component Analysis Video

Week 11

  1. Lecture 51 : Network Data and Random Graph Video
  2. Lecture 52 : Properties of Random Graph Video
  3. Lecture 53 : Law of Large Numbers for Random Graph 1 Video
  4. Lecture 54 : Law of Large Numbers for Random Graph 2 Video
  5. Lecture 55 : Law of Large Numbers for Random Graph 3 Video

Week 12

  1. Lecture 56 : Introduction to Network Medicine Video
  2. Lecture 57 :Selected Case Study on Network Medicine Video
  3. Lecture 58 : Social Network Analysis Video
  4. Lecture 59 : Simple Linear Regression on Social Network Data Video
  5. Lecture 60 : Conclusion and Course Summary Video

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IIT Kharagpur
Department
Computer Science and Engineering
Teacher
Prof. Arindam Banerjee
Level
Undergraduate
Language
English
Subjects
Computer science, Engineering
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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