Forwarded from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค2
PhD Students - Do the following before you start writing your thesis.
๐. ๐๐ฌ๐ ๐๐๐ญ๐๐ฑ, ๐ง๐จ๐ญ ๐๐ ๐๐จ๐ซ๐: Writing a 100+ page document in MS word can become a headache. Arranging headings, tables of content, references, etc can become a challenge. So, instead of MS word, use Latex. It will take care of all such things.
๐. ๐๐๐๐ง๐ญ๐ข๐๐ฒ ๐๐ฑ๐๐ฆ๐ฉ๐ฅ๐๐ซ ๐ญ๐ก๐๐ฌ๐๐ฌ: Before starting your thesis, identify 10-15 exemplar theses that is within your research area or the PhD is carried out in a similar fashion as yours. Skim through them especially the first chapter to understand how to structure your thesis.
๐. ๐๐ฎ๐ข๐ฅ๐ ๐ ๐ฌ๐ญ๐จ๐ซ๐ฒ: During your PhD, you work on different papers that might not be totally linked in a straightforward way. Put these different pieces in front of yourself and think about how to make them link with each other and make a smooth story.
๐. ๐๐ง๐ญ๐ซ๐จ๐๐ฎ๐๐ญ๐ข๐จ๐ง ๐ข๐ฌ ๐ญ๐ก๐ ๐ฆ๐๐ค๐ ๐จ๐ซ ๐๐ซ๐๐๐ค: This chapter summarizes your whole thesis and leaves an impression on the reader/examiner. Invest the most amount of time in writing this chapter. Amongst others, clearly mention upfront the research papers you have published during your PhD.
๐. ๐๐ซ๐ข๐ฌ๐ฉ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ ๐ฌ๐ญ๐๐ญ๐๐ฆ๐๐ง๐ญ ๐๐ง๐ ๐๐จ๐ง๐ญ๐ซ๐ข๐๐ฎ๐ญ๐ข๐จ๐ง๐ฌ: Mention within 3-4 lines the concrete problem you have solved during your PhD. Also, examiners look for 3-4 solid contributions. Don't make them search for them. Present these contributions upfront in the Introduction chapter.
๐. ๐๐ก๐๐ฌ๐ข๐ฌ ๐จ๐ซ๐ ๐๐ง๐ข๐ณ๐๐ญ๐ข๐จ๐ง ๐ฏ๐ข๐ ๐ ๐๐ข๐ ๐ฎ๐ซ๐: PhD thesis is a very long document. Navigating through it can be a challenge. Include a figure in the Introduction section that shows the organization of the thesis including the various chapters. You can check my PhD thesis for such a figure.
๐. ๐๐ฅ๐๐๐ซ๐ฅ๐ฒ ๐ฆ๐๐ง๐ญ๐ข๐จ๐ง ๐ฒ๐จ๐ฎ๐ซ ๐ฉ๐ฎ๐๐ฅ๐ข๐๐๐ญ๐ข๐จ๐ง๐ฌ: If you have published some of your research, mention it upfront in your thesis. This shows to reviewers that part of your research has already been peer-reviewed.
๐. ๐๐๐๐ค ๐๐๐๐๐๐๐๐ค: Manage your writing in a way that each part gets reviewed. If you are running short of time, you can send each chapter separately as it completes to your supervisors for feedback.
๐. ๐๐ก๐จ๐ซ๐จ๐ฎ๐ ๐ก๐ฅ๐ฒ ๐ฉ๐ซ๐จ๐จ๐๐ซ๐๐๐: One of the most common comments from thesis reviewers is to fix the typos. Proofread your entire thesis a couple of times before submission to avoid getting this comment.
๐๐. ๐๐ข๐ง๐ค ๐๐ก๐๐ฉ๐ญ๐๐ซ๐ฌ ๐ญ๐จ ๐๐๐๐ก ๐จ๐ญ๐ก๐๐ซ: Make sure that the chapters are linked together. For example, it shouldn't appear that when the reviewer starts reading chapter 4, it is completely different from chapter 3.
๐. ๐๐ฌ๐ ๐๐๐ญ๐๐ฑ, ๐ง๐จ๐ญ ๐๐ ๐๐จ๐ซ๐: Writing a 100+ page document in MS word can become a headache. Arranging headings, tables of content, references, etc can become a challenge. So, instead of MS word, use Latex. It will take care of all such things.
๐. ๐๐๐๐ง๐ญ๐ข๐๐ฒ ๐๐ฑ๐๐ฆ๐ฉ๐ฅ๐๐ซ ๐ญ๐ก๐๐ฌ๐๐ฌ: Before starting your thesis, identify 10-15 exemplar theses that is within your research area or the PhD is carried out in a similar fashion as yours. Skim through them especially the first chapter to understand how to structure your thesis.
๐. ๐๐ฎ๐ข๐ฅ๐ ๐ ๐ฌ๐ญ๐จ๐ซ๐ฒ: During your PhD, you work on different papers that might not be totally linked in a straightforward way. Put these different pieces in front of yourself and think about how to make them link with each other and make a smooth story.
๐. ๐๐ง๐ญ๐ซ๐จ๐๐ฎ๐๐ญ๐ข๐จ๐ง ๐ข๐ฌ ๐ญ๐ก๐ ๐ฆ๐๐ค๐ ๐จ๐ซ ๐๐ซ๐๐๐ค: This chapter summarizes your whole thesis and leaves an impression on the reader/examiner. Invest the most amount of time in writing this chapter. Amongst others, clearly mention upfront the research papers you have published during your PhD.
๐. ๐๐ซ๐ข๐ฌ๐ฉ ๐ฉ๐ซ๐จ๐๐ฅ๐๐ฆ ๐ฌ๐ญ๐๐ญ๐๐ฆ๐๐ง๐ญ ๐๐ง๐ ๐๐จ๐ง๐ญ๐ซ๐ข๐๐ฎ๐ญ๐ข๐จ๐ง๐ฌ: Mention within 3-4 lines the concrete problem you have solved during your PhD. Also, examiners look for 3-4 solid contributions. Don't make them search for them. Present these contributions upfront in the Introduction chapter.
๐. ๐๐ก๐๐ฌ๐ข๐ฌ ๐จ๐ซ๐ ๐๐ง๐ข๐ณ๐๐ญ๐ข๐จ๐ง ๐ฏ๐ข๐ ๐ ๐๐ข๐ ๐ฎ๐ซ๐: PhD thesis is a very long document. Navigating through it can be a challenge. Include a figure in the Introduction section that shows the organization of the thesis including the various chapters. You can check my PhD thesis for such a figure.
๐. ๐๐ฅ๐๐๐ซ๐ฅ๐ฒ ๐ฆ๐๐ง๐ญ๐ข๐จ๐ง ๐ฒ๐จ๐ฎ๐ซ ๐ฉ๐ฎ๐๐ฅ๐ข๐๐๐ญ๐ข๐จ๐ง๐ฌ: If you have published some of your research, mention it upfront in your thesis. This shows to reviewers that part of your research has already been peer-reviewed.
๐. ๐๐๐๐ค ๐๐๐๐๐๐๐๐ค: Manage your writing in a way that each part gets reviewed. If you are running short of time, you can send each chapter separately as it completes to your supervisors for feedback.
๐. ๐๐ก๐จ๐ซ๐จ๐ฎ๐ ๐ก๐ฅ๐ฒ ๐ฉ๐ซ๐จ๐จ๐๐ซ๐๐๐: One of the most common comments from thesis reviewers is to fix the typos. Proofread your entire thesis a couple of times before submission to avoid getting this comment.
๐๐. ๐๐ข๐ง๐ค ๐๐ก๐๐ฉ๐ญ๐๐ซ๐ฌ ๐ญ๐จ ๐๐๐๐ก ๐จ๐ญ๐ก๐๐ซ: Make sure that the chapters are linked together. For example, it shouldn't appear that when the reviewer starts reading chapter 4, it is completely different from chapter 3.
โค6
Forwarded from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค2
PhD Students - Do you want to learn how to do research?
If yes, check out these free resources.
๐๐ฅ๐ฌ๐๐ฏ๐ข๐๐ซ ๐๐๐ฌ๐๐๐ซ๐๐ก๐๐ซ ๐๐๐๐๐๐ฆ๐ฒ offers free resources.
Here are 10 of my favorite resources.
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฐ๐ซ๐ข๐ญ๐ ๐ ๐ฅ๐ข๐ญ๐๐ซ๐๐ญ๐ฎ๐ซ๐ ๐ซ๐๐ฏ๐ข๐๐ฐ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- What reviewers look for in a literature review?
- How to conceptualize and write a review?
- Common myths about literature reviews.
Link: https://lnkd.in/gRsWFvdy
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ข๐๐๐ง๐ญ๐ข๐๐ฒ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก ๐ ๐๐ฉ๐ฌ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- What is research gap?
- Steps for identifying research gap.
- Tools for identifying research gap.
Link: https://lnkd.in/gvxgD95D
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐๐จ๐ง๐๐ฎ๐๐ญ ๐๐ฏ๐ข๐๐๐ง๐๐-๐๐๐ฌ๐๐ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- What is evidence-based research?
- Stepwise approach for conducting evidence-based research.
- How to enhance reliability of your research?
Link: https://lnkd.in/gMUxXybm
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐๐ข๐ง๐ ๐ซ๐๐ฅ๐๐ฏ๐๐ง๐ญ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก ๐ฉ๐๐ฉ๐๐ซ๐ฌ? (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- How to conduct basic search?
- Save searches and set up alerts.
- How to download and export searches?
Link: https://lnkd.in/gKXauFHr
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฐ๐ซ๐ข๐ญ๐ ๐๐ง ๐๐๐ฌ๐ญ๐ซ๐๐๐ญ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Why a good abstract is important?
- What is ideal length of abstract?
- What to include in the abstract?
Link: https://lnkd.in/g9drbDZF
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฌ๐๐๐ฎ๐ซ๐ ๐๐ฎ๐ง๐๐ข๐ง๐ ? (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- How to write grant application?
- What funders look for in grant applications?
- Tips for winning grants.
Link: https://lnkd.in/g-diuMPv
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฎ๐ฌ๐ ๐๐๐ง ๐๐ ๐ข๐ง ๐ซ๐๐ฌ๐๐๐ซ๐๐ก (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- How has Gen AI impacted research?
- How to use Scopus AI search tool?
- Future of Gen AI in research
Link: https://lnkd.in/gepXEzBf
๐. ๐๐ฎ๐ญ๐ก๐จ๐ซ ๐ฉ๐จ๐ฅ๐ข๐๐ข๐๐ฌ ๐จ๐ง ๐ญ๐ก๐ ๐ฎ๐ฌ๐ ๐จ๐ ๐๐๐ง๐๐ซ๐๐ญ๐ ๐๐ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Ethical cases related to Generative AI
- Opportunities offered by Generative AI
- Risks posed by Generative AI
Link: https://lnkd.in/gT4Xg7yP
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฐ๐ซ๐ข๐ญ๐ ๐๐จ๐ฏ๐๐ซ ๐ฅ๐๐ญ๐ญ๐๐ซ ๐๐จ๐ซ ๐ฒ๐จ๐ฎ๐ซ ๐ฆ๐๐ง๐ฎ๐ฌ๐๐ซ๐ข๐ฉ๐ญ (๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Importance of a good cover letter
- How to write strong cover letter?
- What to include in the cover letter?
Link: https://lnkd.in/gFA_pNkD
๐๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ซ๐๐ฌ๐ฉ๐จ๐ง๐ ๐ญ๐จ ๐ซ๐๐ฏ๐ข๐๐ฐ๐๐ซ๐ฌโ ๐๐จ๐ฆ๐ฆ๐๐ง๐ญ๐ฌ? (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Understanding reviewersโ comments
- How to write response to each comment?
- How to increase your chances of paper acceptance?
Link: https://lnkd.in/gcG7mxrc
If yes, check out these free resources.
๐๐ฅ๐ฌ๐๐ฏ๐ข๐๐ซ ๐๐๐ฌ๐๐๐ซ๐๐ก๐๐ซ ๐๐๐๐๐๐ฆ๐ฒ offers free resources.
Here are 10 of my favorite resources.
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฐ๐ซ๐ข๐ญ๐ ๐ ๐ฅ๐ข๐ญ๐๐ซ๐๐ญ๐ฎ๐ซ๐ ๐ซ๐๐ฏ๐ข๐๐ฐ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- What reviewers look for in a literature review?
- How to conceptualize and write a review?
- Common myths about literature reviews.
Link: https://lnkd.in/gRsWFvdy
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ข๐๐๐ง๐ญ๐ข๐๐ฒ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก ๐ ๐๐ฉ๐ฌ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- What is research gap?
- Steps for identifying research gap.
- Tools for identifying research gap.
Link: https://lnkd.in/gvxgD95D
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐๐จ๐ง๐๐ฎ๐๐ญ ๐๐ฏ๐ข๐๐๐ง๐๐-๐๐๐ฌ๐๐ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- What is evidence-based research?
- Stepwise approach for conducting evidence-based research.
- How to enhance reliability of your research?
Link: https://lnkd.in/gMUxXybm
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐๐ข๐ง๐ ๐ซ๐๐ฅ๐๐ฏ๐๐ง๐ญ ๐ซ๐๐ฌ๐๐๐ซ๐๐ก ๐ฉ๐๐ฉ๐๐ซ๐ฌ? (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- How to conduct basic search?
- Save searches and set up alerts.
- How to download and export searches?
Link: https://lnkd.in/gKXauFHr
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฐ๐ซ๐ข๐ญ๐ ๐๐ง ๐๐๐ฌ๐ญ๐ซ๐๐๐ญ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Why a good abstract is important?
- What is ideal length of abstract?
- What to include in the abstract?
Link: https://lnkd.in/g9drbDZF
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฌ๐๐๐ฎ๐ซ๐ ๐๐ฎ๐ง๐๐ข๐ง๐ ? (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- How to write grant application?
- What funders look for in grant applications?
- Tips for winning grants.
Link: https://lnkd.in/g-diuMPv
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฎ๐ฌ๐ ๐๐๐ง ๐๐ ๐ข๐ง ๐ซ๐๐ฌ๐๐๐ซ๐๐ก (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- How has Gen AI impacted research?
- How to use Scopus AI search tool?
- Future of Gen AI in research
Link: https://lnkd.in/gepXEzBf
๐. ๐๐ฎ๐ญ๐ก๐จ๐ซ ๐ฉ๐จ๐ฅ๐ข๐๐ข๐๐ฌ ๐จ๐ง ๐ญ๐ก๐ ๐ฎ๐ฌ๐ ๐จ๐ ๐๐๐ง๐๐ซ๐๐ญ๐ ๐๐ (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Ethical cases related to Generative AI
- Opportunities offered by Generative AI
- Risks posed by Generative AI
Link: https://lnkd.in/gT4Xg7yP
๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ฐ๐ซ๐ข๐ญ๐ ๐๐จ๐ฏ๐๐ซ ๐ฅ๐๐ญ๐ญ๐๐ซ ๐๐จ๐ซ ๐ฒ๐จ๐ฎ๐ซ ๐ฆ๐๐ง๐ฎ๐ฌ๐๐ซ๐ข๐ฉ๐ญ (๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Importance of a good cover letter
- How to write strong cover letter?
- What to include in the cover letter?
Link: https://lnkd.in/gFA_pNkD
๐๐. ๐๐จ๐ฐ ๐ญ๐จ ๐ซ๐๐ฌ๐ฉ๐จ๐ง๐ ๐ญ๐จ ๐ซ๐๐ฏ๐ข๐๐ฐ๐๐ซ๐ฌโ ๐๐จ๐ฆ๐ฆ๐๐ง๐ญ๐ฌ? (๐๐ ๐ฆ๐ข๐ง ๐ฏ๐ข๐๐๐จ)
You will learn
- Understanding reviewersโ comments
- How to write response to each comment?
- How to increase your chances of paper acceptance?
Link: https://lnkd.in/gcG7mxrc
โค6๐1
Forwarded from Machine Learning with Python
PhD Students - Do you need datasets for your research?
Here are 30 datasets for research from NexData.
Use discount code for 20% off: G5W924C3ZI
1. Korean Exam Question Dataset for AI Training
https://lnkd.in/d_paSwt7
2. Multilingual Grammar Correction Dataset
https://lnkd.in/dV43iqTp
3. High quality video caption dataset
https://lnkd.in/dY9kxkhx
4. 3D models and scenes datasets for AI and simulation
https://lnkd.in/dT-zscH4
5. Image editing datasets โ object removal, addition & modification
https://lnkd.in/dd8iCGMS
6. QA dataset โ visual & text reasoning
https://lnkd.in/dc3TNWFD
7. English instruction tuning dataset
https://lnkd.in/dTeTgd2M
8. Large scale vision language dataset for AI training
https://lnkd.in/dBJuxazN
9. News dataset
https://lnkd.in/dYBJe5gd
10. Global building photos dataset
https://lnkd.in/dVJsDXnC
11. Facial landmarks dataset
https://lnkd.in/dz_KGCS4
12. 3D Human Pose & Landmarks dataset
https://lnkd.in/dXE9ir8Z
13. 3D Hand Pose & Gesture Recognition dataset
https://lnkd.in/d_QdGGb9
14. 14. Driver monitoring dataset โ dangerous, fatigue
https://lnkd.in/d6kF-9PW
15. Japanese handwriting OCR dataset
https://lnkd.in/dHnriqrH
16. American English Male voice TTS dataset
https://lnkd.in/dqyvg862
17. Riddles and brain teasers dataset
https://lnkd.in/dKBHY3DE
18. Chinese test questions text
https://lnkd.in/dQpUd8xC
19. Chinese medical question answering data
https://lnkd.in/dsbWUCpz
20. Multi-round interpersonal dialogues text data
https://lnkd.in/dQiUq_Jg
21. Human activity recognition dataset
https://lnkd.in/dHM52MfV
22. Facial expression recognition dataset
https://lnkd.in/dqQAfMau
23. Urban surveillance dataset
https://lnkd.in/dc2RCnTk
24. Human body segmentation dataset
https://lnkd.in/d6sSrDxS
25. Fashion segmentation โ clothing & accessories
https://lnkd.in/dptNUTz8
26. Fight video dataset โ action recognition
https://lnkd.in/dnY_m5hZ
27. Gesture recognition dataset
https://lnkd.in/dFVPivYg
28. Facial skin defects dataset
https://lnkd.in/dKCbUvU6
29. Smoke detection and behaviour recognition dataset
https://lnkd.in/ddGg56R4
30. Weight loss transformation video dataset
https://lnkd.in/dqqT4ed9
https://t.me/CodeProgrammer๐พ
Here are 30 datasets for research from NexData.
Use discount code for 20% off: G5W924C3ZI
1. Korean Exam Question Dataset for AI Training
https://lnkd.in/d_paSwt7
2. Multilingual Grammar Correction Dataset
https://lnkd.in/dV43iqTp
3. High quality video caption dataset
https://lnkd.in/dY9kxkhx
4. 3D models and scenes datasets for AI and simulation
https://lnkd.in/dT-zscH4
5. Image editing datasets โ object removal, addition & modification
https://lnkd.in/dd8iCGMS
6. QA dataset โ visual & text reasoning
https://lnkd.in/dc3TNWFD
7. English instruction tuning dataset
https://lnkd.in/dTeTgd2M
8. Large scale vision language dataset for AI training
https://lnkd.in/dBJuxazN
9. News dataset
https://lnkd.in/dYBJe5gd
10. Global building photos dataset
https://lnkd.in/dVJsDXnC
11. Facial landmarks dataset
https://lnkd.in/dz_KGCS4
12. 3D Human Pose & Landmarks dataset
https://lnkd.in/dXE9ir8Z
13. 3D Hand Pose & Gesture Recognition dataset
https://lnkd.in/d_QdGGb9
14. 14. Driver monitoring dataset โ dangerous, fatigue
https://lnkd.in/d6kF-9PW
15. Japanese handwriting OCR dataset
https://lnkd.in/dHnriqrH
16. American English Male voice TTS dataset
https://lnkd.in/dqyvg862
17. Riddles and brain teasers dataset
https://lnkd.in/dKBHY3DE
18. Chinese test questions text
https://lnkd.in/dQpUd8xC
19. Chinese medical question answering data
https://lnkd.in/dsbWUCpz
20. Multi-round interpersonal dialogues text data
https://lnkd.in/dQiUq_Jg
21. Human activity recognition dataset
https://lnkd.in/dHM52MfV
22. Facial expression recognition dataset
https://lnkd.in/dqQAfMau
23. Urban surveillance dataset
https://lnkd.in/dc2RCnTk
24. Human body segmentation dataset
https://lnkd.in/d6sSrDxS
25. Fashion segmentation โ clothing & accessories
https://lnkd.in/dptNUTz8
26. Fight video dataset โ action recognition
https://lnkd.in/dnY_m5hZ
27. Gesture recognition dataset
https://lnkd.in/dFVPivYg
28. Facial skin defects dataset
https://lnkd.in/dKCbUvU6
29. Smoke detection and behaviour recognition dataset
https://lnkd.in/ddGg56R4
30. Weight loss transformation video dataset
https://lnkd.in/dqqT4ed9
https://t.me/CodeProgrammer
Please open Telegram to view this post
VIEW IN TELEGRAM
โค4
Forwarded from Machine Learning with Python
Rocket.new lets you build a full website using prompts with their vibe solutioning platform ๐ง โก๏ธ
You describe it, it does the work.
๐ For the first time on this channel: 100% OFF for 2 months
๐ Coupon code:
โ๏ธ Valid on all pricing plans
Go to Rocket.new now, enter the code, claim your 2 months free, or miss out and come back later paying the full subscription.๐ธ
claim your 2 months free
You describe it, it does the work.
X7K2M9P4R1NQGo to Rocket.new now, enter the code, claim your 2 months free, or miss out and come back later paying the full subscription.
claim your 2 months free
Please open Telegram to view this post
VIEW IN TELEGRAM
โค1
PhD Students - Here is an example of a good discussion section.
A good discussion section should answer 6 questions.
1. What is different in your findings compared to previous research?
2. What is similar in your findings compared to previous research?
3. How different sections of your results section correlate?
4. What are the implications of your findings for practitioners?
5. What are the implications of your findings for researchers?
6. What are the limitations or threats to the validity of your findings?
A good discussion section should answer 6 questions.
1. What is different in your findings compared to previous research?
2. What is similar in your findings compared to previous research?
3. How different sections of your results section correlate?
4. What are the implications of your findings for practitioners?
5. What are the implications of your findings for researchers?
6. What are the limitations or threats to the validity of your findings?
โค5
Forwarded from Machine Learning with Python
A collection of basic techniques for working with tensors in PyTorch โ for those who are starting to get acquainted with the framework and want to quickly master its fundamentals.
What's inside:
A good starting material to understand the mechanics of tensors before moving on to models and training.โถ๏ธ What tensors are and why they are neededโถ๏ธ Tensor initialization: zeros, ones, random, similar sizeโถ๏ธ Type conversion and switching between NumPy and PyTorchโถ๏ธ Arithmetic, logical operations, tensor comparisonโถ๏ธ Matrix multiplication and batch computationsโถ๏ธ Broadcasting, view(), reshape(), changing dimensionsโถ๏ธ Indexing and slicing: how to access parts of a tensorโถ๏ธ Notebook with code examples
tags: #useful
Please open Telegram to view this post
VIEW IN TELEGRAM
โค2
This media is not supported in your browser
VIEW IN TELEGRAM
PhD Students โ How to compare 10 papers in 10 seconds?
Meet ๐๐๐ข๐๐ฉ๐๐๐ โ this tool compares papers for you.
Here is how it works.
1. Go to https://lnkd.in/dyirEcYG and log in
2. Click on + ๐ ๐๐๐ and upload the 10 papers.
3. After uploading papers, write your prompt.
๐ถ๐๐๐๐๐๐ ๐กโ๐ ๐ข๐๐๐๐๐๐๐ 10 ๐๐๐ ๐๐๐๐โ ๐๐๐๐๐๐
4. SciSpace will start comparing the papers.
5. You will see the comparison result on right side.
6. Here you will see various insights with paper numbers.
7. At the end, you will see summary of the comparison.
8. SciSpace compares the papers based on:
โ Similarities in research themes
โ Differences in approaches
โ Relative strengths and weaknesses
โ Gaps identified across papers
โ Relationships and building upon each other
9. To trace to each paper, click on the ๐๐๐๐๐ ๐๐ข๐๐๐๐๐
10. To trace to exact location, click on ๐๐๐๐๐ก๐ ๐๐ท๐น.
Where can you use such comparison?
You can use it to:
โ Understand the related literature.
โ Position the novelty of your research paper.
โ Understand niche questions in a research area.
โ Grasp key insights from a bunch of papers in one go.
Try SciSpace today: https://lnkd.in/dyirEcYG
Meet ๐๐๐ข๐๐ฉ๐๐๐ โ this tool compares papers for you.
Here is how it works.
1. Go to https://lnkd.in/dyirEcYG and log in
2. Click on + ๐ ๐๐๐ and upload the 10 papers.
3. After uploading papers, write your prompt.
๐ถ๐๐๐๐๐๐ ๐กโ๐ ๐ข๐๐๐๐๐๐๐ 10 ๐๐๐ ๐๐๐๐โ ๐๐๐๐๐๐
4. SciSpace will start comparing the papers.
5. You will see the comparison result on right side.
6. Here you will see various insights with paper numbers.
7. At the end, you will see summary of the comparison.
8. SciSpace compares the papers based on:
โ Similarities in research themes
โ Differences in approaches
โ Relative strengths and weaknesses
โ Gaps identified across papers
โ Relationships and building upon each other
9. To trace to each paper, click on the ๐๐๐๐๐ ๐๐ข๐๐๐๐๐
10. To trace to exact location, click on ๐๐๐๐๐ก๐ ๐๐ท๐น.
Where can you use such comparison?
You can use it to:
โ Understand the related literature.
โ Position the novelty of your research paper.
โ Understand niche questions in a research area.
โ Grasp key insights from a bunch of papers in one go.
Try SciSpace today: https://lnkd.in/dyirEcYG
โค4
Forwarded from Machine Learning with Python
๐ 23 Years of SPOTO โ Claim Your Free IT Certs Prep Kit!
๐ฅWhether you're preparing for #Python, #AI, #Cisco, #PMI, #Fortinet, #AWS, #Azure, #Excel, #comptia, #ITIL, #cloud or any other in-demand certification โ SPOTO has got you covered!
โ Free Resources :
ใปFree Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS courses: https://bit.ly/4lk4m3c
ใปIT Certs E-book: https://bit.ly/4bdZOqt
ใปIT Exams Skill Test: https://bit.ly/4sDvi0b
ใปFree AI material and support tools: https://bit.ly/46TpsQ8
ใปFree Cloud Study Guide: https://bit.ly/4lk3dIS
๐ Become Part of Our IT Learning Circle! resources and support:
https://chat.whatsapp.com/Cnc5M5353oSBo3savBl397
๐ฌ Want exam help? Chat with an admin now!
wa.link/rozuuw
๐ฅWhether you're preparing for #Python, #AI, #Cisco, #PMI, #Fortinet, #AWS, #Azure, #Excel, #comptia, #ITIL, #cloud or any other in-demand certification โ SPOTO has got you covered!
โ Free Resources :
ใปFree Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS courses: https://bit.ly/4lk4m3c
ใปIT Certs E-book: https://bit.ly/4bdZOqt
ใปIT Exams Skill Test: https://bit.ly/4sDvi0b
ใปFree AI material and support tools: https://bit.ly/46TpsQ8
ใปFree Cloud Study Guide: https://bit.ly/4lk3dIS
๐ Become Part of Our IT Learning Circle! resources and support:
https://chat.whatsapp.com/Cnc5M5353oSBo3savBl397
๐ฌ Want exam help? Chat with an admin now!
wa.link/rozuuw
โค2
This media is not supported in your browser
VIEW IN TELEGRAM
PhD Students โ How to find references for your paper in seconds?
Meet ๐๐ข๐ง๐๐ซ โ a tool that inserts citations in paper.
๐๐จ๐ฐ ๐๐ข๐ง๐๐ซ ๐ฐ๐จ๐ซ๐ค๐ฌ?
1. Go to https://lnkd.in/dsgKZV-P
2. Click on ๐ถ๐๐ก๐๐ก๐๐๐ ๐ ๐๐๐๐๐๐๐๐๐๐ from the left menu
3. Paste the text in which you want to insert citations
4. Now click on ๐บ๐๐๐๐๐๐ก๐ ๐ถ๐๐ก๐๐ก๐๐๐๐
5. Liner will insert citations in your text
๐๐ฌ๐ข๐ง๐ ๐๐ข๐ง๐๐ซ ๐๐จ๐ซ ๐๐ข๐ญ๐๐ญ๐ข๐จ๐ง๐ฌ ๐ก๐๐ฌ ๐ ๐๐๐ฏ๐๐ง๐ญ๐๐ ๐๐ฌ
โ Unlike ChatGPT, it recommends reliable citations
โ The whole process is very transparent
โ The citations automatically get inserted in your text
โ The process is very quick and super easy
Try Liner today for citations: https://lnkd.in/dsgKZV-P
Meet ๐๐ข๐ง๐๐ซ โ a tool that inserts citations in paper.
๐๐จ๐ฐ ๐๐ข๐ง๐๐ซ ๐ฐ๐จ๐ซ๐ค๐ฌ?
1. Go to https://lnkd.in/dsgKZV-P
2. Click on ๐ถ๐๐ก๐๐ก๐๐๐ ๐ ๐๐๐๐๐๐๐๐๐๐ from the left menu
3. Paste the text in which you want to insert citations
4. Now click on ๐บ๐๐๐๐๐๐ก๐ ๐ถ๐๐ก๐๐ก๐๐๐๐
5. Liner will insert citations in your text
๐๐ฌ๐ข๐ง๐ ๐๐ข๐ง๐๐ซ ๐๐จ๐ซ ๐๐ข๐ญ๐๐ญ๐ข๐จ๐ง๐ฌ ๐ก๐๐ฌ ๐ ๐๐๐ฏ๐๐ง๐ญ๐๐ ๐๐ฌ
โ Unlike ChatGPT, it recommends reliable citations
โ The whole process is very transparent
โ The citations automatically get inserted in your text
โ The process is very quick and super easy
Try Liner today for citations: https://lnkd.in/dsgKZV-P
โค5
Forwarded from Machine Learning with Python
This media is not supported in your browser
VIEW IN TELEGRAM
๐๐ข๐ฌ๐ฎ๐๐ฅ ๐๐ฅ๐จ๐ on Vision Transformers is live.
https://vizuaranewsletter.com/p/vision-transformers?r=5b5pyd&utm_campaign=post&utm_medium=web
Learn how ViT works from the ground up, and fine-tune one on a real classification dataset.
๐๐จ๐ฆ๐ ๐๐๐ฌ๐จ๐ฎ๐ซ๐๐๐ฌ
ViT paper dissection
https://youtube.com/watch?v=U_sdodhcBC4
Build ViT from Scratch
https://youtube.com/watch?v=ZRo74xnN2SI
Original Paper
https://arxiv.org/abs/2010.11929
https://t.me/CodeProgrammer
https://vizuaranewsletter.com/p/vision-transformers?r=5b5pyd&utm_campaign=post&utm_medium=web
Learn how ViT works from the ground up, and fine-tune one on a real classification dataset.
CNNs process images through small sliding filters. Each filter only sees a tiny local region, and the model has to stack many layers before distant parts of an image can even talk to each other.
Vision Transformers threw that whole approach out.
ViT chops an image into patches, treats each patch like a token, and runs self-attention across the full sequence.
Every patch can attend to every other patch from the very first layer. No stacking required.
That global view from layer one is what made ViT surpass CNNs on large-scale benchmarks.
๐๐ก๐๐ญ ๐ญ๐ก๐ ๐๐ฅ๐จ๐ ๐๐จ๐ฏ๐๐ซ๐ฌ:
- Introduction to Vision Transformers and comparison with CNNs
- Adapting transformers to images: patch embeddings and flattening
- Positional encodings in Vision Transformers
- Encoder-only structure for classification
- Benefits and drawbacks of ViT
- Real-world applications of Vision Transformers
- Hands-on: fine-tuning ViT for image classification
The Image below shows
Self-attention connects every pixel to every other pixel at once. Convolution only sees a small local window. That's why ViT captures things CNNs miss, like the optical illusion painting where distant patches form a hidden face.
The architecture is simple. Split image into patches, flatten them into embeddings (like words in a sentence), run them through a Transformer encoder, and the class token collects info from all patches for the final prediction. Patch in, class out.
Inside attention: each patch (query) compares itself to all other patches (keys), softmax gives attention weights, and the weighted sum of values produces a new representation aware of the full image, visualizes what the CLS token actually attends to through attention heatmaps.
The second half of the blog is hands-on code. I fine-tuned ViT-Base from google (86M params) on the Oxford-IIIT Pet dataset, 37 breeds, ~7,400 images.
๐๐ฅ๐จ๐ ๐๐ข๐ง๐ค
https://vizuaranewsletter.com/p/vision-transformers?r=5b5pyd&utm_campaign=post&utm_medium=web
๐๐จ๐ฆ๐ ๐๐๐ฌ๐จ๐ฎ๐ซ๐๐๐ฌ
ViT paper dissection
https://youtube.com/watch?v=U_sdodhcBC4
Build ViT from Scratch
https://youtube.com/watch?v=ZRo74xnN2SI
Original Paper
https://arxiv.org/abs/2010.11929
https://t.me/CodeProgrammer
โค5
Forwarded from Machine Learning with Python
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
โค1
Forwarded from Learn Python Coding
This channels is for Programmers, Coders, Software Engineers.
0๏ธโฃ Python
1๏ธโฃ Data Science
2๏ธโฃ Machine Learning
3๏ธโฃ Data Visualization
4๏ธโฃ Artificial Intelligence
5๏ธโฃ Data Analysis
6๏ธโฃ Statistics
7๏ธโฃ Deep Learning
8๏ธโฃ programming Languages
โ
https://t.me/addlist/8_rRW2scgfRhOTc0
โ
https://t.me/Codeprogrammer
Please open Telegram to view this post
VIEW IN TELEGRAM
โค3
๐ฅ2026 New IT Certification Prep Kit โ Free!
SPOTO cover: #Python #AI #Cisco #PMI #Fortinet #AWS #Azure #Excel #CompTIA #ITIL #Cloud + more
โ Grab yours free kit now:
โข Free Courses (Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS)
๐ https://bit.ly/3Ogtn3i
โข IT Certs E-book
๐ https://bit.ly/41KZlru
โข IT Exams Skill Test
๐ https://bit.ly/4ve6ZbC
โข Free AI Materials & Support Tools
๐ https://bit.ly/4vagTuw
โข Free Cloud Study Guide
๐ https://bit.ly/4c3BZCh
๐ฌ Need exam help? Contact admin: wa.link/w6cems
โ Join our IT community: get free study materials, exam tips & peer support
https://chat.whatsapp.com/BiazIVo5RxfKENBv10F444
SPOTO cover: #Python #AI #Cisco #PMI #Fortinet #AWS #Azure #Excel #CompTIA #ITIL #Cloud + more
โ Grab yours free kit now:
โข Free Courses (Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS)
๐ https://bit.ly/3Ogtn3i
โข IT Certs E-book
๐ https://bit.ly/41KZlru
โข IT Exams Skill Test
๐ https://bit.ly/4ve6ZbC
โข Free AI Materials & Support Tools
๐ https://bit.ly/4vagTuw
โข Free Cloud Study Guide
๐ https://bit.ly/4c3BZCh
๐ฌ Need exam help? Contact admin: wa.link/w6cems
โ Join our IT community: get free study materials, exam tips & peer support
https://chat.whatsapp.com/BiazIVo5RxfKENBv10F444
โค1
This media is not supported in your browser
VIEW IN TELEGRAM
PhD Students โ How to write a systematic literature review draft in 1 day?
A systematic literature review takes 4-6 months.
You can reduce this time.
๐ฏ Here is how you can write it in 1 hour.
1๏ธโฃ Go to www.gatsbi.com
2๏ธโฃ Select Gatsbi reviewer from the drop-down menu
3๏ธโฃ Enter the topic of your literature review
4๏ธโฃ Gatsbi will generate an outline for review
5๏ธโฃ If you are OK with it, click on write manuscript.
6๏ธโฃ Gatsbi will write the literature review for you.
๐ The literature review contains the following parts
โ Title
โ Abstract
โ Introduction
โ Methodology
โ Results
โ Discussion
โ Conclusion
โ References
๐ This polished paper also contains
โ Diagrams
โ Tables
โ Equations
โ Graphs
Once the paper is ready, you can humanize the text.
Once humanized, you can download it in the following formats.
โณ MS Word
โณ Latex
โณ Markdown
After downloading, you can make any changes you want.
In addition to Gatsbi Reviewer, you can also use:
โ Gatsbi Innovator: Generate ideas before writing
โ Gatsbi Writer: Write research papers
๐ Try Gatsbi today for free: www.gatsbi.com
โ๏ธ Anything you'd like to add?
#phd #research #literature #review
A systematic literature review takes 4-6 months.
You can reduce this time.
๐ฏ Here is how you can write it in 1 hour.
1๏ธโฃ Go to www.gatsbi.com
2๏ธโฃ Select Gatsbi reviewer from the drop-down menu
3๏ธโฃ Enter the topic of your literature review
4๏ธโฃ Gatsbi will generate an outline for review
5๏ธโฃ If you are OK with it, click on write manuscript.
6๏ธโฃ Gatsbi will write the literature review for you.
๐ The literature review contains the following parts
โ Title
โ Abstract
โ Introduction
โ Methodology
โ Results
โ Discussion
โ Conclusion
โ References
๐ This polished paper also contains
โ Diagrams
โ Tables
โ Equations
โ Graphs
Once the paper is ready, you can humanize the text.
Once humanized, you can download it in the following formats.
โณ MS Word
โณ Latex
โณ Markdown
After downloading, you can make any changes you want.
In addition to Gatsbi Reviewer, you can also use:
โ Gatsbi Innovator: Generate ideas before writing
โ Gatsbi Writer: Write research papers
๐ Try Gatsbi today for free: www.gatsbi.com
โ๏ธ Anything you'd like to add?
#phd #research #literature #review
โค2