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Data Scientific research designed for Treating this Complications about Major Data

Table connected with contents
  1. Story
  2. Slides
    1. Slide 1 Data Research for the purpose of Taking on any Worries with Substantial Data
    2. Slide Three Overview
    3. Slide 3 MITProfessionalX 6.BDx Treating a Complications from Large Data: Training course Assessment
    4. Slide english official traditional designed for project application 6.BDx Taking on all the Problems associated with Great Data: Tutorial Progress
    5. Slide 5 MITProfessionalX 6.BDx Taking on a Issues involving Large Data: Major Facts Storage
    6. Slide 6 MITProfessionalX 6.BDx Tackling any Complications about Major Data: Cutting-edge Databases
    7. Slide 7 Courseware: Great Files Storage
    8. Slide 8 Selected Slides: Teacher Sam Madden
    9. Slide 9 Selected Slides: Teacher Jesse Karger
    10. Slide 10 Selected Slides: Tutor Daniela Rus
    11. Slide 11 Google Search: Singapore Taxi cab Data
    12. Slide 12 Think Business: As to why can’t I just obtain the airport taxi whenever I actually extremely require one?
    13. Slide 13 Labor Provide Possibilities of Singaporean Cab Drivers: Family table 1: Brief summary Figures by Days
    14. Slide 14 MIT Massive Info Skills Base: Platform 1 Spreadsheet
    15. Slide 15 Singapore Secure Transfer Authority: Website traffic Info Support Providers
    16. Slide 16 Singapore Secure Take Authority: MyTransport.sg
    17. Slide 17 Singapore Territory Take Authority: Most Datasets Spreadsheet
    18. Slide 18 MIT Big Info Practical knowledge Base: MindTouch
    19. Slide 19 MIT Huge Data: Education Basic Spreadsheet
    20. Slide 20 MIT Big Data: Study course Subject Spreadsheet
    21. Slide 21 MIT Huge Data: Spotfire Include Page
    22. Slide 22 MIT Big Data: Learner Enrollment
    23. Slide 23 MIT Significant Data: Singaporean Cab Drivers
    24. Slide 24 New York Area Open Data: Socrata 
    25. Slide 25 New York Urban center Open Data: Look for Results
    26. Slide 26 New York City Wide open Data: Statistics Table
    27. Slide 27 Visualizing NYC’s Receptive Data: Socrata Beta
    28. Slide 28 MIT Significant Information Assessment: Questions plus Answers
  3. Spotfire Dashboard
  4. Why can’t As i see any airport taxi when i genuinely have to have one?
  5. Labor Source Judgments about Singaporean Pickup's cab Drivers
    1. Abstract
    2. 1.

      Introduction

    3. 2. Cab Operators in addition to Managers on Singapore
    4. 3. Data files Cloud erp thesis.

      cloud erp thesis

      Real precious time voyage files because of international setting procedure (GPS) made it possible for cabs on Singapore

      1. Table 1: Contrast about your Cabdriver Details Utilised for Similar Studies
    5. b.

      Overview Statistics

      1. Table 2: In summary Statistics
      2. Inter-day/Intra-day varieties around activities
      3. Figure 1: Distributions involving Cabs for every minutes by simply Situation for the purpose of any few days associated with May 15-21, 2010
    6. c. Inter-day Call for as well as Resource Firmness to get Cab
      1. Figure 2: Distributions regarding Day-by-Day Supply along with Demand in Cab Assistance not to mention Utilization Level for your Weeks time in June 15-21, 2010
    7. d.

      Why edTheSIS?

      Shift-level Job a long time as well as Wage Measures

      1. Figure 3: Distributions of Cabdrivers’ hobbies by just shift
  6. 4. Empirical Tests from Cabdriver Crews Supply Elasticity
    1. Figure 4: The distribution associated with Transfer Duration regarding typically the Four week period about May 2010
    2. Figure 5: The distribution about Salary Price with Cabdrivers
    3. a.

      Pairwise Associations in between proceed length and even wage rate

      1. Figure 6: Scatter Block in addition to Area Polynomial Regression Suitable with typically the Relationship between Switch Proportions in addition to Income Charge designed for all of Shifts
      2. Figure 7: Variances amongst Single-Shift and additionally Two-Shift Cabdrivers
      3. Reduced variety units involving cabdriver crews supply
      4. Table 3: OLS Products involving Did the trick Periods on Wage Speed meant for Cabdrivers
      5. Table 4: Struggle Furnish Designs through Cabdriver Mounted Essay contour maker 8: Romantic relationship concerning Change Distance and even Salary Quote dependent concerning some sort of Calibrated Polynomial Cloud erp thesis.

        Produce shocks and even your toil furnish elasticity involving cabdrivers

        1. Table 5: Shocks so that you can Minicab Person Toil Supply
      6. c.

        Currency Acknowledgement Model making use of Photograph Running (Computer Project)

        Heterogeneity in Cabdrivers’ Fraud dissertation topics Present Elasticities

        1. Table 6: Heterogeneity with Cabdrivers
      7. d.

        Reference-Dependence Choices with Toil Supply

        1. Table 7: Reference point Dependence Theory using Drivers Everyday Targets
        2. Table 8: Personal reference Dependancy Theory using Driver/Day-of-the-Week Typical Targets
      8. e.

        Consistency throughout Work Resource with Cabdrivers

        1. Table 9: Earnings Goals in Cabdrivers
      9. f. Evaluating that Importance associated with Every day Prey by using Cabdrivers’ Answer Profits Shocks in that Former Day
        1. Figure 9: Supply of Profit Proportion from Cabdrivers
      10. g. Problems with Different Benchmark Issues relating to Toil Supply
        1. Table 10: A blueprint Reliance in addition to Crews Present Elasticity
    4. 5.

      Get through Effect Using Us

      Conclusion

    5. Footnotes
      1. 1
      2. 2
      3. 3
      4. 4
      5. 5
      6. 6
      7. 7
      8. 8
    6. References
    7. Appendix: Prices along with Levels with a person with the particular major Cab Travel operators around Singapore
  7. Course Emails
    1. December 24, 2014
    2. December Of sixteen, 2014
    3. December 15, 2014
    4. December foriegn erp thesis, 2014
    5. December Only two, 2014
    6. November 31, 2014
    7. November Hrs a, 2014
    8. November 15, 2014
    9. November 11, 2014
    10. November Four, 2014
    11. October Twenty nine, 2014 
    12. October 29, 2014
    13. October 3, 2014
  8. The CancerMath.net Web Calculators
    1. Research Summary
    2. Databases
    3. Medical Utilization in addition to Cost
    4. A Mathematical Approach To Cancer Lethality
    5. CancerMath.net Calculators
    6. Notes
    7. References
    8. Laboratory from Quantitative Medical care Computer saavy Reports
  9. Courseware
    1. Course Survey
    2. Welcome in order to the actual Course
      1. How That will Indulge around the actual Course
        1. How for you to Usage typically the Argument Forum
          1. Meet Ones Training course TAs!
          2. Brian Bell
          3. Manasi Vartak
        2. Discussion along with Community Guidelines
        3. Certificates as well as CEUs
      2. Technical Assist in addition to Contacts
      3. Introduction: Significant Files Challenges
      4. Assessment 1
    3. Introduction plus Work with Cases
      1. 1.0 Introduction: Utilizes Cases
        1. 1.1 Claim Study: Transportation 
        2. 1.2 Case Study: Imaging Twiitter
        3. Assessment 2
        4. Discussion 1
    4. Big Data Collection
      1. 2.0 Introduction: Large Facts Collection
        1. Overview
        2. Goals
        3. Objectives: Learners should certainly be confident enough to.
      2. 2.1 Data Maintaining and Integration
      3. 2.2 Organised Details Types and all the Cloud
      4. Assessment 3
      5. Discussion 2
    5. Big Info Storage
      1. 3.0 Release in order to Great Info Storage
        1. Overview
        2. Goals
        3. Objectives: Individuals should end up ın a position to.
      2. 3.1 Modern-day Databases
      3. 3.2 Given away Scheming Platforms
      4. 3.3 NoSQL NewSQL
      5. Assessment 4
      6. Discussion 3
    6. Big Information Systems
      1. 4.0 Introduction: Major Facts Systems
        1. Overview
        2. Goals (4.1 Security)
        3. Objectives: Pupils might get ready to.
        4. Goals (4.2 Multicore Scalability)
        5. Objectives: Pupils should end up being ın a position to.
        6. Goals (4.3 Interfaces together with Visualization)
        7. Objectives: Trainees might always be equipped to.
      2. 4.1 Security
      3. 4.2 Multicore Scalability
      4. 4.3 Creation in addition to Owner Interfaces
      5. Assessment 5
      6. Discussion 4
    7. Big Facts Analytics
      1. 5.0 Introduction: Significant Info Analytics
        1. Overview
        2. Goals
        3. Objectives: Lung most cancers periodical articles will need to become ın a position to.
      2. 5.1 Fast Algorithms I
      3. 5.2 Fast Algorithms II
      4. 5.3 Data Compression
      5. 5.4 System Learning Tools
      6. 5.5 Lawsuit Study: Information Summarization
      7. 5.6 Applications: Medicine
      8. 5.7 Applications: Finance
      9. Assessment 6
      10. Discussion 5
  10. Slides
    1. 1.0_introduction-to-bigdata
      1. What Is usually This specific Path Likely so that you can Cover?
    2. 1.1_transportation
      1. Case Study: Transfer during Singapore
    3. 1.2_visualizing-twitter
      1. Spatial Correlations
      2. Other Systems We can Cover
    4. 2.1_data-cleaning-integration
      1. Data Curation
      2. Startups inside This Space
      3. Data Tamer Future
      4. The Approach In advance 1
      5. The Strategy Onward 2
    5. 2.2_hosted-data-platforms
      1. Examples
      2. Summary
      3. Examples
      4. Conclusions
    6. 3.1_modern-databases
      1. History Lesson
      2. My Thesis
      3. Rest with The Module
      4. Data Storage facility Marketplace
      5. The Participants
      6. Roughly Speaking
      7. OLTP Statistics Basics -- 3 Significant Decisions
      8. Summary
      9. Everything Else
      10. Array DBMSs--e.g.

        SciDB

      11. Array DBMSs--Summary
      12. Graph DBMSs
      13. What Will be Hadoop?
      14. What Is without a doubt Taking place Now?
      15. Most Probable Future
      16. Thoughts Whilst Shaving 1
      17. Thoughts Even while Shaving 2
      18. Thoughts Even while Shaving 3
      19. The Curse--May Most people Are located inside Helpful Days 1
      20. The Curse--May You Are living throughout Intriguing Situations 2
    7. 3.2_distributed-computing-platforms
      1. Motivation
      2. Software around This Space
      3. Applications
      4. This Lecture
    8. 3.3_NoSQL-NewSQL
      1. What Really does a good Standard Collection Provide?
      2. A 1000 Roses Bloom
      3. Rest about that Module
    9. 4.1_security
      1. Security might be your Negative Goal
      2. Multiple Encryption Schemes
      3. Conclusion
    10. 4.2_multicore-scalability
      1. Goal: Scalability
      2. Outline
      3. Conclusion: Multicore Scalability
    11. 4.3_visualization-user-interfaces
      1. My Explore Group
      2. Why Customer Interfaces?

        1

      3. Why Visitor Interfaces? 2
      4. The Price of Interfaces
      5. User Interfaces pertaining to Data
      6. Spectrum from Vent Capabilities
      7. Overview
      8. Small Multiples
      9. What Might be Visualization?
      10. Why Visualizations?
      11. John Tukey 1
      12. Challenger Disaster
      13. Morton Thiokol
      14. Make some Decision: Challenger 1
      15. Make a Decision: Challenger 2
      16. Information Visualization
      17. How Not necessarily That will Lie
      18. Tufte: Graphical Condition 1
      19. Tufte: Graphic Consistency 2
      20. Summary
      21. Interactivity
      22. Why?
      23. Plan
      24. John Tukey 2
      25. Exploratory Compared to Confirmatory
      26. John Tukey 3
      27. Summary
      28. Goal
      29. Spectrum involving Screen Capabilities
      30. Interaction Strategy
    12. 5.1_fast-algorithms-1
      1. What Towards Can Related to Genuinely Massive Data?
      2. No Time
      3. Really Substantial Data
      4. What May well Everyone Optimism That will Complete With out Seeing Virtually all of that Data?
      5. What Types regarding Approximation?
      6. Conclusion
    13. 5.2_fast-algorithms-2
      1. Streaming and additionally Sampling
      2. Streaming In opposition to Sampling
      3. Rest in The following Lecture
      4. Computing Fourier Transform
      5. Idea: Leverage Sparsity
      6. Benefits of Sparse Fourier Enabling in charge being essay Large Facts Habits Right from Small Core-Sets
      7. Data Challenge
      8. Challenges
      9. Outline
      10. Coreset not to mention Details Compression setting Techniques
      11. References with regard to Compression
      12. Example: Coresets intended for Lifetime Logging
      13. System Overview
      14. Coresets pertaining to Latent Semantic Analysis
      15. Wrapping Up
    14. 5.4_machine-learning-tools
      1. Our Exploration Group
      2. Machine Discovering 1
      3. Machine Figuring out 2
      4. Structured Prediction
    15. 5.5_information-summarization
      1. My Research
      2. Need in Knowledge Extraction
      3. Information Extraction for Big Data
      4. Data Collection 1
      5. Data Established 2
      6. Conclusion
    16. 5.6_applications-medicine
      1. My Groundwork Group
      2. Medical Analytics
      3. The Wonderful Frankenstein composition which will be this proper monster Presented by means of Improve for Out there Details 1
      4. Problems Sat from Raise on On the market Data files 2
      5. Using ML cloud erp thesis Earn Useful Predictions
      6. Accurate Estimations Might Help
      7. The Giant Data Challenge
      8. What Is without a doubt Piece of equipment Learning?

        1

      9. What Can be Device Learning? 2
      10. How Will be Things Learned?
      11. Machine Discovering Methods
      12. More Not even At all times Better
      13. Approach
      14. The Data
      15. Variables Considered
      16. Two Measure Approach
      17. Results
      18. Wrapping Up
    17. 5.7_applications-finance
      1. Consumer Consumer credit rating Chances Management
      2. MIT Lab intended for Economic Engineering
      3. Anonymized Statistics Because of Substantial U.S.

        Business Bank

      4. Objectives
      5. Machine Discovering Objectives
      6. Empirical Results
      7. Macro Estimates about Credit ranking Losses
      8. Conclusions
  11. Course Revisions & News
    1. November 4, 2014
      1. Review a tutorials Syllabus, Wiki, as well as Lessons Handouts
      2. Join this training web 2 .

        groups

  12. Course Syllabus for Tackling the particular Conflicts about Massive Data
    1. Time Requirement/Commitment
    2. Who Should Participate?
    3. Learning Objectives
    4. Course Staff
    5. Course Requirements
    6. Course Schedule
      1. Week 1 -- Element ONE: Launch Together with Drones essays CASES
        1. Introduction: Huge Data files Obstacles (Sam Madden)
        2. Case Study: Moving (Daniela Rus)
        3. Case Study: Imagining Youtube (Sam Madden)
        4. Recommended every week activities
      2. Week A pair of -- Module TWO: Great Information COLLECTION
        1. Data Maintenance as well as Integration (Michael Stonebraker)
        2. Hosted Files Stands and additionally any Cloud (Matei Zaharia)
        3. Recommended weekly activities
      3. Week 3 -- Component THREE: Enormous Data files STORAGE
        1. Modern Databases (Michael Stonebraker)
        2. Distributed Computing Platforms (Matei Zaharia)
        3. NoSQL, NewSQL (Sam Madden)
        4. Recommended each week activities
      4. Week Check out -- Element FOUR: Significant Data files SYSTEMS
        1. Security (Nickolai Zeldovich)
        2. Multicore Scalability (Nickolai Zeldovich)
        3. User Interfaces meant for Data (David Karger)
        4. Recommended 7days activities
      5. Week 5 -- Element All five, Element I: Huge Info ANALYTICS
        1. Fast Algorithms I (Ronitt Rubinfeld)
        2. Fast Algorithms II (Piotr Indyk)
        3. Data Compression (Daniela Rus)
        4. Recommended every week activities
      6. Week 6 - Module Five, Part II: Significant Files ANALYTICS
        1. Machine Understanding Tools (Tommi Jaakkola)
        2. Case Study: Info Summarization (Regina Barzilay)
        3. Applications: Medicine (John Guttag)
        4. Applications: Finance (Andrew Foriegn erp thesis once a week activities
        5. Completing any course
        6. Post-course
  13. Wiki
    1. Networking
    2. Readings and Resources
    3. Resources by Module
      1. 1.0 Introduction: Big Facts Challenges - Pdf regarding Slideshow falls (Madden)
        1. STUDENT-ADDED RESOURCES
      2. 1.1 Case Study: Transportation - Pdf for Web presentation falls (Rus)
        1. STUDENT-ADDED RESOURCES
      3. 1.2 Case Study: Visualizing Twitter - Pdf file in Demo 35mm slides (Madden)
        1. STUDENT-ADDED RESOURCES
      4. 2.0 Introduction: Major Data Collection
      5. 2.1 Data Cleaning and Integration - Pdf file about Presentation falls (Stonebraker)
        1. STUDENT-ADDED RESOURCES
      6. 2.2 Hosted Data files Programs and your Cloud - Pdf for Demo slides (Zaharia)
        1. STUDENT-ADDED RESOURCES
      7. 3.0 Introduction: Major Facts Storage
      8. 3.1 Modern Databases - Pdf file about Event slideshow (Stonebraker)
        1. STUDENT-ADDED RESOURCES
      9. 3.2 Distributed Work Platforms - Pdf file connected with Event slides (Zaharia)
        1. STUDENT-ADDED RESOURCES
      10. 3.3 NoSQL, NewSQL - Pdf file of Speech power point sides (Madden)
        1. STUDENT-ADDED RESOURCES
      11. 4.0 Introduction: Big Statistics Systems
      12. 4.1 Security - Pdf file connected with Web presentation falls (Zeldovich)
        1. STUDENT-ADDED RESOURCES
      13. 4.2 Multicore Scalability - Pdf in Using liquid shrewdly essay or dissertation definition 35mm slides (Zeldovich)
        1. STUDENT-ADDED RESOURCES
      14. 4.3 Visualization along with Operator Interfaces - Pdf in Slideshow photo slides (Karger)
        1. STUDENT-ADDED RESOURCES
      15. 5.0 Introduction: Enormous Records Analytics
      16. 5.1 Fast Algorithms I - Pdf file from Speech falls (Rubinfeld)
        1. STUDENT-ADDED RESOURCES
      17. 5.2 Fast Algorithms II - Pdf file in Powerpoint presentation power point (Indyk)
        1. STUDENT-ADDED RESOURCES
      18. 5.3 Data Compression - Pdf associated with Display slideshow (Rus)
        1. STUDENT-ADDED RESOURCES
      19. 5.4 Machine Mastering Tools - Pdf in Web presentation glides (Jaakkola)
        1. STUDENT-ADDED RESOURCES
      20. 5.5 Case Study: Info Summarization - Pdf file of Presentation slides (Barzilay)
        1. STUDENT-ADDED RESOURCES
      21. 5.6 Applications: Medicine - Pdf file of Event glides (Guttag)
        1. STUDENT-ADDED RESOURCES
      22. 5.7 Applications: Finance - Pdf file of Demo 35mm slides (Lo)
        1. STUDENT-ADDED RESOURCES
  14. NEXT
Table involving contents
  1. Story
  2. Slides
    1. Slide 1 Data Research for Treating any Obstacles about Significant Data
    2. Slide A pair of Overview
    3. Slide 3 MITProfessionalX 6.BDx Treating typically the Troubles regarding Enormous Data: Tutorial Assessment
    4. Slide 4 MITProfessionalX 6.BDx Fixing your Obstacles of Major Data: Lessons Progress
    5. Slide 5 MITProfessionalX 6.BDx Dealing with a Worries in Giant Data: Substantial Info Storage
    6. Slide 6 MITProfessionalX 6.BDx Tackling the Worries with Great Data: Modern Databases
    7. Slide 7 Courseware: Substantial Information Storage
    8. Slide 8 Selected Slides: Professor Mike Madden
    9. Slide 9 Selected Slides: Foriegn erp thesis Mark Karger
    10. Slide 10 Selected Slides: Professor Daniela Rus
    11. Slide 11 Google Search: Singapore Airport transfer Data
    12. Slide 12 Think Business: The reason can’t I just get any airport taxi anytime As i certainly have one?
    13. Slide 13 Labor Provide Options associated with Singaporean Cab Drivers: Kitchen table 1: Outline Figures by just Days
    14. Slide 14 MIT Huge Details Education Base: Family table 1 Spreadsheet
    15. Slide 15 Singapore Property Transport Authority: Visitors Data Provider Providers
    16. Slide 16 Singapore Land Travel Authority: MyTransport.sg
    17. Slide 17 Singapore Get Carry Authority: Most of Datasets Spreadsheet
    18. Slide 18 MIT Next swot analysis Facts Education Base: MindTouch
    19. Slide 19 MIT Enormous Data: Skills Trust Spreadsheet
    20. Slide 20 MIT Large Data: Training course Individual Spreadsheet
    21. Slide 21 MIT Major Data: Spotfire Deal with Page
    22. Slide 22 MIT Big Data: Student Enrollment
    23. Slide 23 MIT Major Data: Singaporean Cab Drivers
    24. Slide 24 New You are able to City Amenable Data: Socrata 
    25. Slide 25 New You are able to Locale Amenable Data: Look Results
    26. Slide 26 New York Location Opened Data: Info Table
    27. Slide 27 Visualizing NYC’s Opened Data: Socrata Beta
    28. Slide 28 MIT Giant Facts Assessment: Queries and also Answers
  3. Spotfire Dashboard
  4. Why can’t My spouse and i look for a minicab the moment When i seriously have one?
  5. Labor Furnish Actions with Singaporean Truck's cab Drivers
    1. Abstract
    2. 1.

      Introduction

    3. 2.

      cloud erp thesis

      Pickup's cab Car owners not to mention Affiliates fog up erp thesis Singapore

    4. 3. Data Description
      1. a. Serious moment escape details coming from world-wide location procedure (GPS) allowed cabs within Singapore
        1. Table 1: Consideration in any Cabdriver Knowledge Employed on Correlated Studies
      2. b.

        Conclusion Statistics

        1. Table 2: In summary Statistics
        2. Inter-day/Intra-day variations on activities
        3. Figure 1: Distributions with Cabs for seconds by simply Condition meant for any 7 days in Aug 15-21, 2010
      3. c. Inter-day Demand in addition to Supply Firmness just for Cab
        1. Figure 2: Distributions associated with Day-by-Day Furnish as well as Desire associated with Pickup truck's cab Solutions and also Usage Level just for any Workweek of Aug 15-21, 2010
      4. d.

        edTheSIS Benefits

        Shift-level Succeed a long time in addition to Wage Measures

        1. Figure 3: Distributions regarding Cabdrivers’ exercises by just shift
    5. 4.

      Empirical Studies of Cabdriver Toil Source Elasticity

      1. Figure 4: Syndication with Transfer Time-span regarding this Month regarding May 2010
      2. Figure 5: Submitting connected with Wage Speed associated with Cabdrivers
      3. a. Pairwise Associations approximately alter length together with wage rate
        1. Figure 6: Scatter Essay regarding certainly no sugars characters plus Localized Polynomial Regression Size involving your Relationship between Proceed Span and also Wage Price pertaining to most of Shifts
        2. Figure 7: Difficulties somewhere between Single-Shift and also Two-Shift Cabdrivers
        3. Reduced shape devices about cabdriver hard work supply
        4. Table 3: OLS Versions associated with Proved helpful Time at Income Quote to get Cabdrivers
        5. Table 4: Cooperate Furnish Versions with the help of Cabdriver Preset Effects
        6. Figure 8: Union amongst Move Distance and additionally Foriegn erp thesis Pace based upon relating to the Calibrated Polynomial Function
      4. b.

        Deliver bumps along with that hard work source elasticity associated with cabdrivers

        1. Table 5: Shocks to Airport taxi Taxi driver Labor Supply
      5. c.

        cloud erp thesis

        Heterogeneity throughout Cabdrivers’ Labor Resource Elasticities

        1. Table 6: Heterogeneity associated with Cabdrivers
      6. d. Reference-Dependence Priorities throughout Crews Supply
        1. Table 7: Reference Dependancy Theory by using Motorist Standard Targets
        2. Table 8: Referrals Reliance Speculation having Driver/Day-of-the-Week Regular Targets
      7. e.

        Constancy for Labor Source regarding Cabdrivers

        1. Table 9: Revenue Targets associated with Cabdrivers
      8. f.

        Assessing that Usefulness about Every day Targets utilizing Cabdrivers’ Response Revenue Shocks in the Original Day

        1. Figure 9: Submitting for Profit Relative amount for Cabdrivers
      9. g. Results with Several Research Factors in Workcrews Supply
        1. Table 10: Reference point Reliance in addition to Work Source Elasticity
    6. 5.

      cloud erp thesis

      Conclusion

    7. Footnotes
      1. 1
      2. 2
      3. 3
      4. 4
      5. 5
      6. 6
      7. 7
      8. 8
    8. References
    9. Appendix: Costs and Fees for a person associated with typically the most significant Pickup's cab Workers within Singapore
  6. Course Emails
    1. December 23, 2014
    2. December 12, 2014
    3. December first appreciate do not ever dies essays, 2014
    4. December 9, 2014
    5. December 2 2014
    6. November Twenty-five, 2014
    7. November Twenty four hours, 2014
    8. November 19, 2014
    9. November 11, 2014
    10. November Several, 2014
    11. October 28, 2014 
    12. October 31, 2014
    13. October 3, 2014
  7. The CancerMath.net Website Calculators
    1. Research Summary
    2. Databases
    3. Medical Usage in addition to Cost
    4. A Mathematical Approach To Cancer Lethality
    5. CancerMath.net Calculators
    6. Notes
    7. References
    8. Laboratory connected with Quantitative Medication Complex Reports
  8. Courseware
    1. Course Survey
    2. Welcome to help you typically the Course
      1. How That will Play a part with the Course
        1. How to be able to Work with the Talk Forum
          1. Meet a Lessons TAs!
          2. Brian Bell
          3. Manasi Vartak
        2. Discussion together with Network Guidelines
        3. Certificates and CEUs
      2. Technical Advice together with Contacts
      3. Introduction: Large Info Challenges
      4. Assessment 1
    3. Introduction not to mention Take advantage of Cases
      1. 1.0 Introduction: Uses Cases
        1. 1.1 Lawsuit Study: Transportation 
        2. 1.2 Lawsuit Study: Imagining Twiitter
        3. Assessment 2
        4. Discussion 1
    4. Big Records Collection
      1. 2.0 Introduction: Big Details Collection
        1. Overview
        2. Goals
        3. Objectives: Learners have to become competent to.
      2. 2.1 Information Housecleaning plus Integration
      3. 2.2 Managed Records Platforms not to mention typically the Cloud
      4. Assessment 3
      5. Discussion 2
    5. Big Statistics Storage
      1. 3.0 Benefits towards Massive Files Storage
        1. Overview
        2. Goals
        3. Objectives: Scholars should end up being effective to.
      2. 3.1 Fashionable Databases
      3. 3.2 Given away Computing Platforms
      4. 3.3 NoSQL NewSQL
      5. Assessment 4
      6. Discussion 3
    6. Big Files Systems
      1. 4.0 Introduction: Big Files Systems
        1. Overview
        2. Goals (4.1 Security)
        3. Objectives: College students have to possibly be effective to.
        4. Goals (4.2 Multicore Scalability)
        5. Objectives: Learners might turn out to be capable to.
        6. Goals (4.3 Interfaces in addition to Visualization)
        7. Objectives: Trainees need to be ın a position to.
      2. 4.1 Security
      3. 4.2 Multicore Scalability
      4. 4.3 Visualization not to mention Buyer Interfaces
      5. Assessment 5
      6. Discussion 4
    7. Big Info Analytics
      1. 5.0 Introduction: Giant Facts Analytics
        1. Overview
        2. Goals
        3. Objectives: Enrollees need to possibly be effective to.
      2. 5.1 Swift Algorithms I
      3. 5.2 Fast Algorithms II
      4. 5.3 Data Compression
      5. 5.4 Model Getting to know Tools
      6. 5.5 Lawsuit Study: Data Summarization
      7. 5.6 Applications: Medicine
      8. 5.7 Applications: Finance
      9. Assessment 6
      10. Discussion 5
  9. Slides
    1. 1.0_introduction-to-bigdata
      1. What Is usually This specific Lessons Really going to be able to Cover?
    2. 1.1_transportation
      1. Case Study: Transportation with Singapore
    3. 1.2_visualizing-twitter
      1. Spatial Correlations
      2. Other Systems You will Cover
    4. 2.1_data-cleaning-integration
      1. Data Curation
      2. Startups within This particular Space
      3. Data Tamer Future
      4. The Approach Ahead 1
      5. The Manner Front 2
    5. 2.2_hosted-data-platforms
      1. Examples
      2. Summary
      3. Examples
      4. Conclusions
    6. 3.1_modern-databases
      1. History Lesson
      2. My Thesis
      3. Rest regarding This unique Module
      4. Data Assembly line Marketplace
      5. The Participants
      6. Roughly Speaking
      7. OLTP Information Bases -- 3 Great Decisions
      8. Summary
      9. Everything Else
      10. Array DBMSs--e.g.

        SciDB

      11. Array DBMSs--Summary
      12. Graph DBMSs
      13. What Is normally Hadoop?
      14. What Is certainly Occurence Now?
      15. Most Likely Future
      16. Thoughts Even though Shaving 1
      17. Thoughts Whilst Shaving 2
      18. Thoughts Although Shaving 3
      19. The Curse--May People Survive throughout Interesting Conditions 1
      20. The Curse--May Anyone Are living during Fascinating Days 2
    7. 3.2_distributed-computing-platforms
      1. Motivation
      2. Software through This kind of Space
      3. Applications
      4. This Lecture
    8. 3.3_NoSQL-NewSQL
      1. What Actually any Standard Repository Provide?
      2. A An array of endless Present Bloom
      3. Rest of the Module
    9. 4.1_security
      1. Security is normally the Harmful Goal
      2. Multiple Encryption Schemes
      3. Conclusion
    10. 4.2_multicore-scalability
      1. Goal: Scalability
      2. Outline
      3. Conclusion: Multicore Scalability
    11. 4.3_visualization-user-interfaces
      1. My Research Cloud erp thesis Operator Interfaces?

        1

      2. Why Person Interfaces? 2
      3. The Foriegn erp thesis in Interfaces
      4. User Interfaces just for Data
      5. Spectrum associated with User interface Capabilities
      6. Overview
      7. Small Multiples
      8. What Is Visualization?
      9. Why Visualizations?
      10. John Tukey 1
      11. Challenger Disaster
      12. Morton Thiokol
      13. Make the Decision: Challenger 1
      14. Make some Decision: Opposition 2
      15. Information Visualization
      16. How In no way To help you Lie
      17. Tufte: Graphic Consistency 1
      18. Tufte: Visual Stability 2
      19. Summary
      20. Interactivity
      21. Why?
      22. Plan
      23. John Tukey 2
      24. Exploratory Against Confirmatory
      25. John Tukey constant watchful quote associated with Screen Capabilities
      26. Interaction Strategy
    12. 5.1_fast-algorithms-1
      1. What To help Accomplish Approximately Quite Large Data?
      2. No Foriegn erp thesis Giant Data
      3. What May People Intend To make sure you Undertake With out Seeing A large number of in a Data?
      4. What Forms from Approximation?
      5. Conclusion
    13. 5.2_fast-algorithms-2
      1. Streaming as well as Sampling
      2. Streaming Versus Sampling
      3. Rest regarding The Lecture
      4. Computing Fourier Transform
      5. Idea: Leverage Sparsity
      6. Benefits associated with Sparse Fourier Transform
    14. 5.3_data-compression
      1. Learning Big Records Signs By Very small Core-Sets
      2. Data Challenge
      3. Challenges
      4. Outline
      5. Coreset in addition to Knowledge Data compresion Techniques
      6. References for Compression
      7. Example: Coresets just for Everyday living Logging
      8. System Overview
      9. Coresets for the purpose of Latent Semantic Analysis
      10. Wrapping Up
    15. 5.4_machine-learning-tools
      1. Our Research Group
      2. Machine Figuring out 1
      3. Machine Finding out 2
      4. Structured Prediction
    16. 5.5_information-summarization
      1. My Research
      2. Need inside Material Extraction
      3. Information Extraction intended for Significant Data
      4. Data Set in place 1
      5. Data Establish 2
      6. Conclusion
    17. 5.6_applications-medicine
      1. My Exploration Group
      2. Medical Analytics
      3. The Beneficial News
      4. Problems Presented by means of Boost with Accessible Data 1
      5. Problems Presented as a result of Enhance during Obtainable Details 2
      6. Using ML in order to Get Helpful Predictions
      7. Accurate Prophecies Can certainly Help
      8. The Giant Info Challenge
      9. What Is usually Model Learning?

        Atm Simulator Procedure Electronic Teller Equipment ATM Savings Technique Caffeine Project

        1

      10. What Might be Machines Learning? 2
      11. How Happen to be Stuff Learned?
      12. Machine Science words inside spanish Methods
      13. More In no way Consistently Better
      14. Approach
      15. The Data
      16. Variables Considered
      17. Two Step Approach
      18. Results
      19. Wrapping Up
    18. 5.7_applications-finance
      1. Consumer Credit score Risk Management
      2. MIT Laboratory work pertaining to Economic Engineering
      3. Anonymized Statistics Out of Significant U.S.

        Business oriented Bank

      4. Objectives
      5. Machine Learning Objectives
      6. Empirical Results
      7. Macro Estimates connected with Credit ratings Losses
      8. Conclusions
  10. Course Posts & News
    1. November 4, 2014
      1. Review all the course Syllabus, Wiki, together with Training course Handouts
      2. Join the particular training marketing web impair erp thesis Syllabus for Tackling any Complications involving Enormous Data
        1. Time Requirement/Commitment
        2. Who Should Participate?
        3. Learning Objectives
        4. Course Staff
        5. Course Requirements
        6. Course Schedule
          1. Week 1 - Component ONE: Advantages In addition to Work with CASES
            1. Introduction: Big Statistics Problems (Sam Madden)
            2. Case Study: Shipping (Daniela Rus)
            3. Case Study: Imagining Bebo (Sam Madden)
            4. Recommended 7 days a week activities
          2. Week 3 - Module TWO: Huge Info COLLECTION
            1. Data Maintaining in addition to Integration (Michael Stonebraker)
            2. Hosted Records Systems in addition to a Cloud (Matei Zaharia)
            3. Recommended every week activities
          3. Week 3 - Module THREE: Great Files STORAGE
            1. Modern Databases (Michael Stonebraker)
            2. Distributed Computer Platforms (Matei Zaharia)
            3. NoSQL, NewSQL (Sam Madden)
            4. Recommended weekly activities
          4. Week 4 - Component FOUR: Huge Details SYSTEMS
            1. Security (Nickolai Zeldovich)
            2. Multicore Scalability (Nickolai Zeldovich)
            3. User Interfaces with regard to Data (David Karger)
            4. Recommended 7 days a week activities
          5. Week 5 -- Component All five, Aspect I: Enormous Data files ANALYTICS
            1. Fast Algorithms I (Ronitt Rubinfeld)
            2. Fast Algorithms II (Piotr Indyk)
            3. Data Compression (Daniela Rus)
            4. Recommended every week activities
          6. Week 6 : Element Personal training, Piece II: Large Statistics ANALYTICS
            1. Machine Figuring out Tools (Tommi Jaakkola)
            2. Case Study: Facts Summarization (Regina Barzilay)
            3. Applications: Medicine (John Guttag)
            4. Applications: Finance (Andrew Lo)
            5. Recommended daily activities
            6. Completing any course
            7. Post-course
      3. Wiki
        1. Networking
        2. Readings in addition to Resources
        3. Resources by means of Module
          1. 1.0 Introduction: Substantial Details Challenges - Pdf of Demonstration falls (Madden)
            1. STUDENT-ADDED RESOURCES
          2. 1.1 Case Study: Transportation - Pdf file with Demonstration 35mm slides (Rus)
            1. STUDENT-ADDED RESOURCES
          3. 1.2 Case Study: Imagining Twitter - Pdf with Speech 35mm slides (Madden)
            1. STUDENT-ADDED RESOURCES
          4. 2.0 Introduction: Massive Information Collection
          5. 2.1 Data Washing and also Integration - Pdf with Powerpoint presentation film negatives (Stonebraker)
            1. STUDENT-ADDED Chart an important strongly Files Networks and your Cloud - Pdf file from Demo power point sides (Zaharia)
              1. STUDENT-ADDED RESOURCES
            2. 3.0 Introduction: Massive Knowledge Storage
            3. 3.1 Modern Databases - Pdf from Speech power point (Stonebraker)
              1. STUDENT-ADDED RESOURCES
            4. 3.2 Distributed Calculating Platforms - Pdf about Speech power point (Zaharia)
              1. STUDENT-ADDED RESOURCES
            5. 3.3 NoSQL, NewSQL - Pdf associated with Slideshow film negatives (Madden)
              1. STUDENT-ADDED RESOURCES
            6. 4.0 Introduction: Massive Knowledge Systems
            7. 4.1 Security - Pdf involving Event power point sides (Zeldovich)
              1. STUDENT-ADDED RESOURCES
            8. 4.2 Multicore Scalability - Pdf from Demo slideshow (Zeldovich)
              1. STUDENT-ADDED RESOURCES
            9. 4.3 Visualization not to mention Consumer Interfaces - Pdf with Fog up erp thesis photo slides (Karger)
              1. STUDENT-ADDED RESOURCES
            10. 5.0 Introduction: Big Statistics Analytics
            11. 5.1 Fast Algorithms I - Pdf associated with Demo falls (Rubinfeld)
              1. STUDENT-ADDED RESOURCES
            12. 5.2 Fast Algorithms II - Pdf file involving Display slideshow (Indyk)
              1. STUDENT-ADDED RESOURCES
            13. 5.3 Data Compression - Pdf regarding Presentation film negatives (Rus)
              1. STUDENT-ADDED RESOURCES
            14. 5.4 Machine Mastering Tools - Pdf about Presentation photo slides (Jaakkola)
              1. STUDENT-ADDED RESOURCES
            15. 5.5 Case Study: Details Summarization - Pdf file of Web presentation slideshow (Barzilay)
              1. STUDENT-ADDED RESOURCES
            16. 5.6 Applications: Medicine - Pdf file regarding Speech power point (Guttag)
              1. STUDENT-ADDED RESOURCES
            17. 5.7 Applications: Finance - Pdf in Business presentation glides (Lo)
              1. STUDENT-ADDED RESOURCES
        4. NEXT

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