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Varsha's engineering stuff
India
Приєднався 6 гру 2011
Being profession in teaching for last 17 years, never thought of youtube video creation. During corona virus pandemic, idea comes to my mind of video creation for my students and just for luck uploaded video on UA-cam.
I got surprised by getting positive response from viewers. I thankful to them. Give me suggestions for improvement.
My name is Dr. Varsha Patil, Ph.D. in Image Processing from Mumbai University.
Have expertise in Image Processing, Data Mining, Machine Learning, Natural Language Processing and many more.
If you really like my channel, subscribe and share the link with your friends.
I got surprised by getting positive response from viewers. I thankful to them. Give me suggestions for improvement.
My name is Dr. Varsha Patil, Ph.D. in Image Processing from Mumbai University.
Have expertise in Image Processing, Data Mining, Machine Learning, Natural Language Processing and many more.
If you really like my channel, subscribe and share the link with your friends.
Part 2: Logistic Regression, Gradient Descent, Log Likelihood, Sigmoid
Logistic Regression, Gradient Descent, Log Likelihood, Sigmoid
Переглядів: 147
Відео
Logistic Regression, Sigmoid Function, Binary Classification
Переглядів 1522 місяці тому
Logistic Regression, Sigmoid Function, Binary Classification
Multivariate Linear Regression, Multivariate Simple & Multiple Linear Regression
Переглядів 2312 місяці тому
Multivariate Linear Regression Multivariate Single/Simple Regression Multivariate Multiple Linear Regression
Linear Regression: Gradient Descent Approach, Learning rate, parameters, Simple and Multiple
Переглядів 1532 місяці тому
Linear Regression : Gradient Descent Approach, Gradient, Learning rate, parameters
Part 6: Support Vector Machine, Soft Margin, Parameter C, Ski, Penalty, Lineraly separable
Переглядів 1113 місяці тому
Part 6: Support Vector Machine, Soft Margin, Parameter C, Ski, Penalty, Lineraly separable
Part V: Support Vector Machine, Quadratic Programming, Toy Example, Support vectors,w,b,unseen sampl
Переглядів 2163 місяці тому
Part V: Support Vector Machine, Quadratic Programming, Toy Example, Support vectors,w,b,unseen sampl
Part IVSupport Vector MachineQuadratic Programming
Переглядів 1923 місяці тому
Part IVSupport Vector MachineQuadratic Programming
Part 3: Support Vector Machine, Multiclass, One-vs-Rest, One-vs-One, Error-Correcting Output Codes
Переглядів 2743 місяці тому
Part 3: Support Vector Machine, Multiclass, One-vs-Rest, One-vs-One, Error-Correcting Output Codes
Part 2: Support Vector Machine, Margin, Support Vectors, Boundary, Hyperplane, Simple Problem in 2D
Переглядів 1643 місяці тому
Part 2: Support Vector Machine, Margin,Boundary,Hyperplane
Part 1: Support Vector Machine, Constrained Optimization, Margin, Support vectors, decision boundary
Переглядів 7793 місяці тому
Constrained Optimization Introduction to Support Vector Machine (SVM) Optimal Decision Boundary Margins and Support Vectors
Part 9: Introduction to NLP, Challenges in NLP Application development
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Part 9: Introduction to NLP, Challenges in NLP Application development Accuracy, Scalability, Efficiency, Robustness, Adaptability, Contextual Understanding, Bias Mitigation Interoperability, Multimodal Integration, Data Privacy, User Personalization, Resource Optimization
Part 8: Introduction to NLP at various Levels in Marathi and Hindi Languages
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Part 8: Introduction to NLP at various Levels in Marathi and Hindi Languages
PART 7: Introduction to NLP, Ambiguities, English, Lexical, Syntactic, Semantic, Pragmatic,Discourse
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PART 7:Introduction to NLP, Ambiguities, English, Lexical, Syntactic, Semantic, Prgamatic, Discourse
Part 6: Introduction to NLP, Why NLP is hard, Textual Humor, Sarcasm, Idioms, Neologisms, Tokenizati
Переглядів 1855 місяців тому
Textual Humor Sarcasm Tricky Entity Names Idioms Neologisms Segmentation Issues New Senses of a word Non standard use of English [ e.g. Informal, Shortform] New Senses of a word Words or Phrases: Multiway Interprtation (Confusing Meanings) Language Imprecision and Vagueness Extreme examples of Lexical Ambiguity
Part 5: Introduction to NLP, Language, Grammar and Knowledge in NLP
Переглядів 2495 місяців тому
Part 5: Introduction to NLP, Language, Grammar and Knowledge in NLP
Part 4: History of NLP, First Era, Second Era, Third Era, Fourth Era, Introduction to NLP
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Part 4: History of NLP, First Era, Second Era, Third Era, Fourth Era, Introduction to NLP
NLP Introduction Part 3: Generic NLP System, Parser, Semantic, Pragmatic. & Discourse, Reasoner
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NLP Introduction Part 3: Generic NLP System, Parser, Semantic, Pragmatic. & Discourse, Reasoner
NLP Introduction Part I:Definition,Natural Language Generation(NLG)& Understanding(NLU), Need, Goals
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NLP Introduction Part I:Definition,Natural Language Generation(NLG)& Understanding(NLU), Need, Goals
Semantic Analysis Part 3:Relations among lexemes & their Senses, NLP, Homonymy, Polysemy, Syno,
Переглядів 5866 місяців тому
Semantic Analysis Part 3:Relations among lexemes & their Senses, NLP, Homonymy, Polysemy, Syno,
Part 1: Semantic Analysis, NLP, Computational, Distributional, Formal Semantics, Lexicon & Lexeme
Переглядів 7656 місяців тому
Part 1: Semantic Analysis, NLP, Computational, Distributional, Formal Semantics, Lexicon & Lexeme
Part 7: Earley Parser, Top Down Parser, NLP, Predict, Scan, Complete, Chart, Tanle, CFG Rule
Переглядів 2,6 тис.6 місяців тому
Part 7: Earley Parser, Top Down Parser, NLP, Predict, Scan, Complete, Chart, Tanle, CFG Rule
Parser Part 6: Predictive Parser, Top Down, NLP, First, Follow, Stack, look ahead, Predictive Table
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Parser Part 6: Predictive Parser, Top Down, NLP, First, Follow, Stack, look ahead, Predictive Table
Part 5: PCFG parser, Bottom Up Parser, NLP, CFG, Probability, CYK Algorithm, Parse Trees Exercises
Переглядів 2,7 тис.6 місяців тому
Part 5: PCFG parser, Bottom Up Parser, NLP, CFG, Probability, CYK Algorithm, Parse Trees Exercises
Part 4: Bottom Up Parser, Shift Reduce Parser, Stack, Shift, Reduce, Ambiguity, Backtracking exercis
Переглядів 9716 місяців тому
Part 4: Bottom Up Parser, Shift Reduce Parser, Stack, Shift, Reduce, Ambiguity, Backtracking exercis
Parser Part 3: Bottom Up, COCKE-YOUNGER-KASAMI (CYK or CKY Parser), NLP, CNF, CFG, Tree, Dynamic
Переглядів 2,2 тис.6 місяців тому
Parser Part 3: Bottom Up, COCKE-YOUNGER-KASAMI (CYK or CKY Parser), NLP, CNF, CFG, Tree, Dynamic
Part 2: NLP Parsers, Modelling Constituency, CFG, Chomsky Normal Form (CNF), Top down & Bottom Up
Переглядів 1,5 тис.6 місяців тому
Part 2: NLP Parsers, Modelling Constituency, CFG, Chomsky Normal Form (CNF), Top down & Bottom Up
Part 1: Parsers in NLP, Parsers Role,Words & Word Groups (Constituency),Types of Parsers, Ambiguity
Переглядів 1,6 тис.6 місяців тому
Part 1: Parsers in NLP, Parsers Role,Words & Word Groups (Constituency),Types of Parsers, Ambiguity
Good Turing Discounting, Smoothing, C*, P*GT, Backoff, Interpolation, Laplace, MLE, NLP
Переглядів 2 тис.6 місяців тому
Good Turing Discounting, Smoothing, C*, P*GT, Backoff, Interpolation, Laplace, MLE, NLP
Part 6: Image Processing Introduction, Connectivity, Adjacency, Euclidean, City Block, Chess Board,m
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Part 6: Image Processing Introduction, Connectivity, Adjacency, Euclidean, City Block, Chess Board,m
Part 5: Image Processing Introduction, IMAGE FILE FORMATS, TIFF, BMP, JPEG, Features, Adv, Disadv
Переглядів 636 місяців тому
Part 5: Image Processing Introduction, IMAGE FILE FORMATS, TIFF, BMP, JPEG, Features, Adv, Disadv
In Q 2) BP(3), min_sup is 2, so it should be frequent? Right? In The table × ✓ ✓ ( frequent, closed, maximal) for BP
Minor mistakes from my side in one problem. From theory and other problems take reference
Awesome. you are my God. Wonderful explanation and one stop portal for NLP basics....
So sweet of you. Thanks for a such lovely comment
ex11 is correct?
i will check
good job.
Thanks!
thank you mam
thank you
how S->aA?
how to divide ?
Thanks. Which test can be used for one dependant variable and multiple independent variable?
f test
Not even one line understood
good video
Thank you for watching!
it was easy with example
Thank you mam
22:00 important point note plz laplace smoothing
Excellent Explanation.
Thank you
Mam after table formation (Using mahattan formula) Probably we get values as whole numbers If e=1.9 If there are no points less than 1.9 How to continue the problem
When calculating ( justin will spot will) in the second side of formula P(POS2|POS1) how exactly are you reading the state transition Matrix sometimes u say it's from top to left side but u take values from left to top side for justin u took value from left to top for will u took left to top for spot suddenly u took from top to left it's confusing how to read transition Matrix please specify fast coz when I'm taking value from top to left side answers are becoming different
Please reply fast ma'am
You just Yapp
It is very difficult to get material for this topic and understanding the topic. Initial part is theory but necessary
great explanation
Glad you liked it
best video for this topic by far. Exactly what cam in my exams ://
In 18:30 why u have wrote 1/3 for P(M|N) when its actually 1/4 in table ?
i will check. by mistake can be possible, see other steps
@@varshasengineeringstuff4621 yea I was stuck there too table is 1/4
we should always take centroid, right??
why average is not taken in first example and taken in other examples for relevant and non-relavant caluculations?
just wanted to mention that i'm referring your nlp playlist, and it has been incredibly helpful in my preparation. Your explanations are clear and easy to follow, which has made even the complex topics much easier to understand. I truly appreciate the effort you put into making these resources available. thanks alot ma'am!
🙌
Thank you
you are a life saver mam, cant thank you enough, I am from Fr.CRCE and I got IR exam tomorrow.
"Thank you so much for your kind words! 😊 Wishing you the very best for your IR exam tomorrow. If you find my content helpful, feel free to share it with your friends and team, and don’t forget to subscribe to the channel for more support. 🌟 All the best!"
After searching for 4 hours, I finally understood good turing after ur video. Thanku
You are most welcome
Ma'am, formula is wrong for calculation of probabilities is it? I think few operations need to be performed in the power of e...
I have taken NPTEL reference. Yes, different calculations can be possible. Only main aim to understand we can use not only limited words POS(forward or backward from current word) but also with reference to other words features
one of the worst videos on internet
:)
thank you this video helped a lot
You're welcome!
+45 and -45 are swapped
By mistake
9:19 In the 3-itemset the frequency of BCD should be 3 and not 4.As BC is closed item set none of its immediate superset can have the same min sup.
I will check. SOme minor mistake may be from my side. ONly my purpose is to explain basic concept
Great explanation!👍👍
Thank you
Are we multiplying the average everywhere(I mean all equations)? I am asking because in formula it is given sigma which means sum.
How is 2/log(5) = 0 in the final table? Any specific reason for that or it's just a mistake?
by mistake
Plz understand steps.
great ❤🔥🔥
thank you
Good morning mam. Do you have notes and ppts of information retrieval please share. Thank you in advance mam.
Good explanation mam🎉
Thanks a lot
I was waiting for this topic, very nicely explained. Thank you for sharing. 🎉🎉
Varsha mam, awesome content, very knowledgeable, kindly share more videos. Thank you madam 🎉
Good one
Thanks for the visit
nice ppt representation mam but if you provide the ppt in description then it better for us
Thank you ❤
Thanks. I guess You are from swat valley of Pakistan. It is very beautiful,
@@varshasengineeringstuff4621 I am 18th descendent of Last King of Swat Sultanate but unfortunately royal family had to leave Swat so we are living in nearby city of Swat now. Thank you for amazing words about our valley ❤️❤️
Thank you for sharing your connection to such a rich heritage. It’s fascinating to learn that you are the 18th descendant of the last King of Swat Sultanate, and I can only imagine the legacy your family carries. Swat Valley’s beauty, culture, and history are truly remarkable, and it’s heartening to know that your family remains part of its story.
@@varshasengineeringstuff4621 We are now landlords of neighboring Mansehra District which is way more beautiful than Swat. The famous Valleys like Naran Kaghan Valley, Siran Valley etc are situated in Mansehra.
Mansehra truly sounds captivating, especially with gems like Naran, Kaghan, and Siran Valley. Mansehra Rock Edicts are fourteen edicts of the Mauryan emperor Ashoka. It’s wonderful that you are part of such a beautiful and renowned region!
now i understand mam thank you
Ppt ?
GREAT
Thank you dear
I have subscribed your channel and i hope that you will post more n more usefull videos regarding digital image processing of jtnua btech ASAP thank you and good job🎉 ... You explained in a nice way.... ❤
Sure. If possible share link of syllabus
@@varshasengineeringstuff4621 Sure thank you very much
dap.jntua.ac.in/wp-content/uploads/2022/07/JNTUA-R20-B.Tech_.-ECE-III-IV-Course-structure-Syllabus.pdf
Please upload videos on digital image processing ASAP
2: Pixel relationship Week 3: Camera models & imaging geometry Week 4: Image interpolation Week 5: Image transformation Week 6: Image enhancement I Week 7: Image enhancement II Week 8: Image enhancement III Week 9: Image restoration I Week 10: Image restoration II & Image registration Week 11: Colour image processing Week 12: Image segmentation Week 13: Morphological image processing Week 14: Object representation ,description and recognition BOOKS AND REFERENCES Digital Image Processing by Rafael C Gonzalez & Richard E Woods, 3rd Edition Fundamentals of Digital Image Processing by Anil K Jain Digital Image Processing by William K Pratt If you do videos on nptel topics in digital image processing I will surely give you 20 subscribers I found your explanation is simple and clear in the whole videos that is why I am request and I hope you will try 😊thank you once again 🎉❤
Very well explained. Thankyou madam.
Thank you dear
unclear
???
exactly i am very much confused in this subject different formulas for same thing
Hello ma'am. I love your teaching 🎉🎉 Is there any textbook you got this from or just from the internet? Could you please recommend the textbook(s) if any?
Thanks for the nice complement. Yes. Manning and Daniel Jurafsky books. Pawan Goyal NPTEL course on NLP
@@varshasengineeringstuff4621 Thanks a lot ma'am.