Skip to main content

ALl in one site

 20 websites to download research projects/thesis.


Download, read, learn and cite👇


1. Open Access Theses and Dissertations (OATD) - https://oatd.org/

2. ProQuest Open Access Dissertations & Theses - https://pqdtopen.proquest.com/

3. Networked Digital Library of Theses and Dissertations (NDLTD) - http://www.ndltd.org/

4. DART-Europe E-theses Portal - https://www.dart-europe.org/

5. EThOS (British Library) - https://ethos.bl.uk/

6. MIT Theses - https://dspace.mit.edu/handle/1721.1/7582

7. OpenThesis - http://www.openthesis.org/

8. OhioLINK Electronic Theses and Dissertations Center - https://etd.ohiolink.edu/

9. CaltechTHESIS - https://thesis.library.caltech.edu/

10. Harvard DASH - https://dash.harvard.edu/

11. University of Michigan Deep Blue - https://deepblue.lib.umich.edu/

12. University of Florida Institutional Repository - https://ufdc.ufl.edu/ufir

13. KU ScholarWorks (University of Kansas) - https://kuscholarworks.ku.edu/

14. Adelaide Research & Scholarship - https://digital.library.adelaide.edu.au/

15. ANU Open Research (Australian National University) - https://openresearch-repository.anu.edu.au/

16

. Utrecht University Repository - https://dspace.library.uu.nl/

17. MacSphere (McMaster University) - https://macsphere.mcmaster.ca/

18. University of Pretoria Electronic Theses and Dissertations - https://repository.up.ac.za/handle/2263/31741

19. TSpace (University of Toronto) - https://tspace.library.utoronto.ca/

20. University of Helsinki E-thesis - https://ethesis.helsinki.fi/en

Comments

Popular posts from this blog

Python road map

 

Ways of pandas making faster

 FireDucks makes Pandas 125x Faster (changing one line of code) 🧠 Pandas has some major limitations: - Pandas only uses a single CPU core. - It often creates memory-heavy DataFrames. - Its eager (immediate) execution prevents global optimization of operation sequences. FireDucks is a highly optimized, drop-in replacement for Pandas with the same API.  There are three ways to use it: 1) Load the extension:  ↳ %𝐥𝐨𝐚𝐝_𝐞𝐱𝐭 𝗳𝗶𝗿𝗲𝗱𝘂𝗰𝗸𝘀.𝐩𝐚𝐧𝐝𝐚𝐬; 𝗶𝗺𝗽𝗼𝗿𝘁 𝗽𝗮𝗻𝗱𝗮𝘀 𝗮𝘀 𝗽𝗱 2) Import FireDucks instead of Pandas:  ↳ 𝐢𝐦𝐩𝐨𝐫𝐭 𝗳𝗶𝗿𝗲𝗱𝘂𝗰𝗸𝘀.𝐩𝐚𝐧𝐝𝐚𝐬 𝐚𝐬 𝐩𝐝 3) If you have a Python script, execute is as follows:  ↳ 𝗽𝘆𝘁𝗵𝗼𝗻3 -𝗺 𝗳𝗶𝗿𝗲𝗱𝘂𝗰𝗸𝘀.𝗽𝗮𝗻𝗱𝗮𝘀 𝗰𝗼𝗱𝗲.𝗽𝘆 Done! ✔️ A performance comparison of FireDucks vs. DuckDB, Polars, and Pandas is shown in the video below. Official benchmarks indicate: ↳ Modin: ~1.0x faster than Pandas ↳ Polars: ~57x faster than Pandas ↳ FireDucks: ~125x faster than Pandas Credit- Ultan...

Top excel formula,master it