Modules / Lectures
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Assignment-2_noc18_cs39_19Assignment-2_noc18_cs39_19
Assignment-3_noc18_cs39_32Assignment-3_noc18_cs39_32
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Sl.No Chapter Name MP4 Download Transcript Download
1Lecture 1 Background: IntroductionDownloadDownload
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2Lecture 2 : Probability: Concentration inequalitiesDownloadDownload
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3Lecture 3 : Linear algebra: PCA, SVDDownloadDownload
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4Lecture 4 : Optimization: Basics, Convex, GDDownloadDownload
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5Lecture 5 : Machine Learning: Supervised, generalization, feature learning, clustering.DownloadDownload
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6Lecture 6 : Memory-efficient data structures: Hash functions, universal / perfect hash familiesDownloadDownload
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7Lecture 7 : Bloom filtersDownloadDownload
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8Lecture 8 : Sketches for distinct countDownloadDownload
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9Lecture 9 : Sketches for distinct count (Contd.)DownloadDownload
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10Lecture 10 : Misra-Gries sketchDownloadDownload
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11Lecture 11 : Frequent Element: Space Saving and Count Min.DownloadDownload
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12Lecture 12 : Frequent Element: Count SketchDownloadDownload
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13Lecture 13 : Near NeighborsDownloadDownload
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14Lecture 14 : Locality Sensitive Hashing.DownloadDownload
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15Lecture 15 : Building LSH Tables.DownloadDownload
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16Lecture 16 : Approximate near neighbors search: Extensions e.g. multi-probe, b-bit hashing, Data dependent variants DownloadDownload
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17Lecture 17 : Approximate near neighbors search: Extensions e.g. multi-probe, b-bit hashing, Data dependent variants (Contd.)DownloadDownload
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18Lecture 18 : Approximate near neighbors search: Extensions e.g. multi-probe, b-bit hashing, Data dependent variants (Contd.)DownloadDownload
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19Lecture 19 : Randomized Numerical Linear Algebra: Random projection DownloadDownload
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20Lecture 20 : Randomized Numerical Linear Algebra: Random projection (Contd.)DownloadDownload
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21Lecture 21: "Randomized Numerical Linear Algebra:a) Matrix multiplication + QB decomposition"DownloadDownload
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22Lecture 22: "Randomized Numerical Linear Algebra:b) CUR+CX"DownloadDownload
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23Lecture 23: "Randomized Numerical Linear Algebra:a) L2 regression using RP"DownloadDownload
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24Lecture 24: "Randomized Numerical Linear Algebra:b) Leverage scores"DownloadDownload
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25Lecture 25: "Randomized Numerical Linear Algebra:c) Hash Kernels + Kitchen Sink"DownloadDownload
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26Lecture 26 : Map-reduce and HadoopDownloadDownload
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27Lecture 27 : Hadoop SystemDownloadDownload
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28Lecture 28 : Hadoop System(Contd.)DownloadDownload
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29Lecture 29 : Hadoop System(Contd.)DownloadDownload
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30Lecture 30 : SparkDownloadDownload
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31Lecture 31 : Spark(Contd.)DownloadDownload
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32Lecture 32 : Spark(Contd.)DownloadDownload
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33Lecture 33 : Distributed Machine Learning and Optimization: IntroductionDownloadDownload
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34Lecture 34 : SGD+ProofDownloadDownload
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35Lecture 35 : SGD+Proof(Contd.)DownloadDownload
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36Lecture 36 : Distributed Machine Learning and Optimization:ADMM + applicationsDownloadDownload
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37Lecture 37 : Distributed Machine Learning and Optimization:ADMM + applications(Contd.)DownloadDownload
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38Lecture 38 : ClusteringDownloadDownload
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39Lecture 39 : Clustering(Contd.)DownloadDownload
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40Lecture 40 : ConclusionDownloadDownload
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