计算机代考程序代写 scheme python database COMP3430_Sem2_2021: generate-student-datasets-rl.py – cscodehelp代写

COMP3430_Sem2_2021: generate-student-datasets-rl.py

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COMP3430/COMP8430 – Data Wrangling – Sem 2 2021

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COMP3430_Sem2_2021

Topic 6

generate-student-datasets-rl.py

generate-student-datasets-rl.py
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◄ dw_assignment_master_rlgt.csv.gz

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Setup necessary software to use in practical labs
Lecture 1 slides (PDF) – Overview and course introduction
Recording lecture 1, part 1 (WEBM format)
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Lecture 2 slides (PDF) – The data wrangling process and understanding data
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Lecture 3 slides (PDF) – Data extraction and storage, data warehousing
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Interactive lecture 1 slides (PDF) – Overview and administrative issues
Week 1 Interactive Lecture
Data Cleaning: Problems and Current Approaches (Rahm and Do, 2000)
For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights ( Times, 2014)

Sample python scripts (for you to get an understanding of the level of Python we use during the practical lab sessions)
Lecture 4 slides (PDF) – Web scraping and geocoding of data
Recording lecture 4, part 1 (WEBM format)
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Lecture 6 slides (PDF) – Resolving data quality issues and data cleaning
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Week 2 Interactive Lecture Slides (PDF)
Week 2 Interactive Lecture 2 Interactive Lecture Recording
Data quality in context (Strong, Lee and Wang, 1997)
Quiz 1 (covering material from weeks 1 and 2)
Assignment 1 Specification
dw_assignment_master.csv.gz
generate-student-dataset.py
student-check-codes-assign1.txt

Lab signup (opens Monday 2 August 4 pm)
Lecture 7 slides (PDF) – Data transformation, aggregation and reduction
Recording lecture 7, part 1 (WEBM format)
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Lecture 8 slides (PDF) – Data parsing and standardisation
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Lecture 9 slides (PDF) – Data pre-processing using Rattle and Python
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Week 3 Review Lecture Slides (PDF)
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Week 3 Review Lecture Demo
Towards Reliable Interactive Data Cleaning: A User Survey and Recommendations (Krishnan, Haas, Franklin and Wu, 2016) (copy)
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Lecture 10 slides (PDF) – Overview of data integration
Additional material for lecture 10: WOO: A Scalable and Multi-tenant Platform for Continuous Knowledge Base Synthesis (Bellare et al., 2013)
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Lecture 11 slides (PDF) – Schema mapping and matching
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Lecture 12 slides (PDF) – Overview of record linkage
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Week 4 Interactive Lecture Slides (PDF)
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Data matching – Chapters 1 and 2 (Christen, 2012)
Lab 2 (week 4) Specification
Lecture 13 slides (PDF) – Data cleaning for record linkage and blocking (1)
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Lecture 14 slides (PDF) – Blocking / indexing (2)
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Quiz 2 (covering material from weeks 2 to 5)
Lecture 15 slides (PDF) – Record pair comparison (1)
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Lecture 16 slides (PDF) – Record pair comparison (2)
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Week 6 Interactive Lecture Recording
Interactive lecture 6 slides 2021
Lab 3 (week 6) Specification
comp3430_comp8430-reclink-lab-3-6.zip (Data sets and Python record linkage programs)
SLK-581 guide for usage
Example solution blocking.py
Lab 3 slides

Assignment 1 submission
General marking feedback assignment 1
Assignment 2 Specification
dw_assignment_master2.csv.gz
generate-student-dataset2.py
student-check-codes-assign2.txt
Education data set description
Assignment 3 Specification
dw_assignment_master_rl1.csv.gz
dw_assignment_master_rl2.csv.gz
dw_assignment_master_rlgt.csv.gz
student-check-codes-assign3.txt
Assignment 4 Specification (

COMP8430 students only)
Adaptive Temporal Entity Resolution on Dynamic Databases (Christen and Gayler, 2013)
Efficient Interactive Training Selection for Large-Scale Entity Resolution (Wang, Vatsalan, and Christen, 2015)
Improving Temporal Record Linkage Using Regression Classification (Hu, Wang, Vatsalan, and Christen, 2017)
Pattern-Mining Based Cryptanalysis of Bloom Filters for Privacy-Preserving Record Linkage (Christen, Vidanage, Ranbaduge, and Schnell, 2018)
A Scalable and Efficient Subgroup Blocking Scheme for Multidatabase Record Linkage (Ranbaduge, Vatsalan, and Christen, 2018)
Robust Temporal Graph Clustering for Group Record Linkage (Nanayakkara, Christen, and Ranbaduge, 2019)
Secure and Accurate Two-Step Hash Encoding for Privacy-Preserving Record Linkage (Ranbaduge, Christen, and Schnell, 2020)
Lecture 17 slides (PDF) – Record pair classification (1)
Recording lecture 17 (WEBM format)
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Lecture 18 slides (PDF) – Record pair classification (2)
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Week 7 Interactive Lecture Recording
Interactive lecture 7 slides
Lab 4 (week 7) specification
Example solution comparison.py
Lab 4 slides
Lecture 19 slides (PDF) – Record linkage evaluation (1)
Recording lecture 19, part 1 (WEBM format)
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Lecture 20 slides (PDF) – Record linkage evaluation (2)
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Recording lecture 20 (MP4 format)
Week 8 Interactive Lecture Recording
Interactive lecture 8 slides
Quiz 3 (covering material from weeks 6 to 8)
Lab 5 (week 8) specification
Example solution classification.py
Lab 5 slides
Lecture 21 slides (PDF) – Data fusion
Recording lecture 21 (WEBM format)
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Lecture 22 slides (PDF) – Advanced record linkage techniques
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Lecture 23 slides (PDF) – Privacy aspects in data wrangling and privacy-preserving record linkage
Recording lecture 23 (WEBM format)
Recording lecture 23 (MP4 format)
Week 9 Interactive Lecture Recording
Interactive lecture 9 slides
Privacy-preserving record linkage using Bloom filters

Assignment 2 submission
Lab 6 (week 9) specification
Example solution evaluation.py
Lab 6 slides
Lecture 24 slides (PDF) – Ontology matching
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Lecture 25 slides (PDF) – Wrangling dynamic and spatial data
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Interactive lecture 10
Interactive lecture 10 slides
Lab 7 (week 10) specification
comp3430_comp8430-reclink-lab7-datasets.zip
Python module saveLinkResult.py
Lab 7 slides
Extra lab specification (for those who are intersted)
Python module privacyPreservingRecordLinkage.py

Assignment 3 submission

Assignment 4 submission (COMP8430 students only!)

student-check-codes-assign3.txt ►

COMP3430_Sem2_2021

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