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Coursera - Mining Massive Datasets (Stanford University) . - aretr - 05-31-2019

[Image: 1905271219580117.jpg]

Coursera - Mining Massive Datasets (Stanford University)
WEBRip | English | MP4 + PDF Guides | 960 x 540 | AVC ~77 kbps | 29.970 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | 20:04:35 | 2.39 GB
Genre: eLearning Video / Data Science and Big Data
We introduce the participant to modern distributed file systems and MapReduce, including what distinguishes good MapReduce algorithms from good algorithms in general. The rest of the course is devoted to algorithms for extracting models and information from large datasets. Participants will learn how Google's PageRank algorithm models importance of Web pages and some of the many extensions that have been used for a variety of purposes.

We'll cover locality-sensitive hashing, a bit of magic that allows you to find similar items in a set of items so large you cannot possibly compare each pair. When data is stored as a very large, sparse matrix, dimensionality reduction is often a good way to model the data, but standard approaches do not scale well; we'll talk about efficient approaches. Many other large-scale algorithms are covered as well, as outlined in the course syllabus.

Syllabus

Week 1:
MapReduce
Link Analysis - PageRank

Week 2:
Locality-Sensitive Hashing - Basics + Applications
Distance Measures
Nearest Neighbors
Frequent Itemsets

Week 3:
Data Stream Mining
Analysis of Large Graphs

Week 4:
Recommender Systems
Dimensionality Reduction

Week 5:
Clustering
Computational Advertising

Week 6:
Support-Vector Machines
Decision Trees
MapReduce Algorithms

Week 7:
More About Link Analysis - Topic-specific PageRank, Link Spam.
More About Locality-Sensitive Hashing

General
Complete name : 06_Dimensionality_Reduction-_Introduction_12-01.mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom (isom/iso2/avc1/mp41)
File size : 18.4 MiB
Duration : 12 min 1 s
Overall bit rate : 214 kb/s
Writing application : Lavf55.19.104

Video
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Format profile : [email protected]
Format settings : CABAC / 4 Ref Frames
Format settings, CABAC : Yes
Format settings, RefFrames : 4 frames
Codec ID : avc1
Codec ID/Info : Advanced Video Coding
Duration : 12 min 1 s
Bit rate : 77.0 kb/s
Width : 960 pixels
Height : 540 pixels
Display aspect ratio : 16:9
Frame rate mode : Constant
Frame rate : 29.970 (29970/1000) FPS
Color space : YUV
Chroma subsampling : 4:2:0
Bit depth : 8 bits
Scan type : Progressive
Bits/(Pixel*Frame) : 0.005
Stream size : 6.62 MiB (36%)
Writing library : x264 core 138
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Language : English

Audio
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Format : AAC
Format/Info : Advanced Audio Codec
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Codec ID : mp4a-40-2
Duration : 12 min 1 s
Bit rate mode : Constant
Bit rate : 128 kb/s
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Sampling rate : 44.1 kHz
Frame rate : 43.066 FPS (1024 SPF)
Compression mode : Lossy
Stream size : 11.0 MiB (60%)
Language : English
Default : Yes
Alternate group : 1

Screenshots

[Image: 1905271219590112.jpg]

[Image: 1905271220010115.jpg]

[Image: 1905271220020105.jpg]
DOWNLOAD

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