- Видео 47
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Machine Learning- Sudeshna Sarkar
Добавлен 18 май 2016
Introduction to Machine Learning:
This channel gives an overview of the course and its organisation. This is followed by a brief discussion of the history of machine learning and its relevance in the present day world. The general workflow of machine learning and a few domains of application are also described.
This channel gives an overview of the course and its organisation. This is followed by a brief discussion of the history of machine learning and its relevance in the present day world. The general workflow of machine learning and a few domains of application are also described.
Видео
Agglomerative Hierarchical Clustering
Просмотров 34 тыс.7 лет назад
Agglomerative Hierarchical Clustering
Python Exercise on kmeans clustering
Просмотров 21 тыс.7 лет назад
Python Exercise on kmeans clustering
Sample Complexity: Finite Hypothesis Space
Просмотров 34 тыс.7 лет назад
Sample Complexity: Finite Hypothesis Space
Introduction to Computational Learning Theory
Просмотров 57 тыс.7 лет назад
Introduction to Computational Learning Theory
Neural Network and Backpropagation Algorithm
Просмотров 62 тыс.7 лет назад
Neural Network and Backpropagation Algorithm
i will like to met or chat with you privately about my work please
i was able to answer first question s unsupervised learning but i missed the second step answer
jaane wo kaise log the jinke dimaag ko yeh samajhne ki shakti mila, hamne to jab seekhna chaha kathinaaiyo ka saamna kara *crying emoji *
This is probably the best decision tree explanation I've come accross. Thank you madam.
I am not able to find the tutorial for the Week 5. Where can I find it?
19:58 what is rt in these formulas?
Thanks a lot maam for providing such quality lectures. Those who have to study proper theoretical ML will truly appreciate these lectures.
Thanks a lot
bhai starting me itna romantic gaana kyu baja rahe ho😭😭😭
Ma'am, thanks for your brief introduction
Your language is tough ma'am please use simple language
The best professor!! I love your classes, thank you for your hard work.
From Bangladesh
Ki sundor kore bojhacchen apni...Pranam neben
Why youtube doesn't have ×10 fast forward ⏩ options
Im will not going for IIT now, Dump teacher
mam's knowledge>sir knowledge but....... sir's teaching ability>>>mam's ability
Bhai bot ganda padhaya, kisi ki baaton par mat jao. Mahendra huddar se padh lo
Shes a beautiful woman so by the way, and im 28😂
I have to train my computer to do coding in the form of class identifiers and relations classes. Which is best. Thanks.
14:24 maam shouldnt it be max of all functional margin as we want the largest distance from the decision boundary/surface for better classification? why min, i didnt understand.
Isn't feature selection same as decision trees? where we select best features as tree grows and conclude when we certain homogeneity is reached?
16:00
Ma'am please consider the feedback in the comments section, you are hampering the image of IIT
worst proff. No effort to make students understand
tere bas ki baat nahi hain AI/ML tu kuchh aur karle
Do we have slides/notes available of this course?
8:51 it would be 0.008 for P(cancer)
7:25
How is y (-ve) , x (+ve) z (+ve) different from y (+ve) , x (-ve) z (-ve)
Nice teaching
How to join this course
Shocking that 7 years ago there's person was talkimg about this, since ChatGPT booming just lately
Booooooooooooooooooooooooring
Queen 👑 Amazing explanation
Finally someone who's not showing a power point
Bias and Variance are so simple topics , this lecture has made it more complicated.
pure knowledge , thanks mam for such amazing lecture.
great lecture ma'am . Thank you so much and happy teacher day, Pronam niben.
mam you teaches awesome but one thing that i suggest you can you improve your black board ,improve your camera so we can see clearly
Very well explained...........This is GOLD ❤
why cant we just check generalization on test data without introducing validation set
Bad teaching
Great Instructor , poor cameraman
I am not from computer science background and I am having trouble in understanding of the concepts😢. I am literally struggling hard to understand the concept and what ma'am is saying. It took me almost 1.5hrs to complete a 30min video even at 2x speed and still understood only 10% of it. Someone please tell me if I need any prior knowledge before getting into this course or any other alternative so that I can grasp the concepts. My feedback: If you have no prior knowledge of ML or if you are a non cs background student. Please don't think to join this course, It would be or it will be the one of the most boring lecture you have ever watched. Edit: I watched next of the lectures at normal and 1.5x speed and it made it a little easy to understand, but still I am not able to solve the assignments.
🙄🙄just watch it on normal it is simple no prior knowledge you need to understand a machine is doing everything on a algo why are you bothering?
Different opinion but to me a good teacher is he/she who can explain and talk about the subject without any materials like notes or ppts, ex. Trainer in REPUTED coaching institute,,,
Watch Andrew NG's lectures CS229 he's also referred notes and other material and i hope you know who he's.
@@jiviteshvarshney3644 that is why i called as worst teaching methodology
very good explanation mam. Thank You So Much.
Excellently covered the topic. Which textbook reference ma'am
very nicely explained lecture! Thank you Mam.
Writing what is written in the book and reading the same thing is not what teaching is.
Useless Lecture. She is even referring to the materials and writing wrong on board.