Subalalitha C N
Subalalitha C N
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Deep Learning Series - Lecture #2
In this video we will have a quick intro about how to train a neural network using back propagation .
Reference : Alexander Amini and Ava Soleimany, MIT 6.S191: Introduction to Deep Learning -IntroToDeepLearning.com
If you are interested in building cool Natural Language Processing Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us at info@firstlanguage.in
Переглядів: 245

Відео

Deep Learning Series - Lecture #1
Переглядів 2472 роки тому
In this video we will have a quick intro about Deep Learning and it's building blocks . Reference : Alexander Amini and Ava Soleimany, MIT 6.S191: Introduction to Deep Learning -IntroToDeepLearning.com If you are interested in building cool Natural Language Processing Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us ...
Policy Iteration algorithm (with worked out example) -Reinforcement Learning Lecture #2
Переглядів 9 тис.3 роки тому
This video is about the Policy Iteration Algorithm in Reinforcement Learning that helps to find the optimal policy. The example problem is referred from towardsdatascience.com/policy-iteration-in-rl-an-illustration-6d58bdcb87a7. If you are interested in building cool Natural Language Processing Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultati...
Markov Decision process (MDP)- Introduction to Reinforcement Learning Master - RL Lecture #1
Переглядів 4,3 тис.3 роки тому
This video is about the Markov Decision Process and this is an introductory video on Reinforcement Learning. If you are interested in building cool Natural Language Processing Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us at info@firstlanguage.in
Multiple Linear Regression Using Gradient Descent
Переглядів 8 тис.4 роки тому
This video is about multiple linear regression using gradient descent. If you are interested in building cool Natural Language Processing (NLP) Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us at info@firstlanguage.in
0 1 Knapsack using Branch and Bound
Переглядів 1,3 тис.4 роки тому
This video is about 0 1 Knapsack using Branch and Bound
Breadth First Search
Переглядів 1174 роки тому
This video is about Breadth First Search traversal of graphs
Depth First Search
Переглядів 864 роки тому
This video is about Depth First Search traversal of graph
Floyd Warshall Algorithm
Переглядів 1364 роки тому
This video is about Floyd Warshall Algorithm
Travelling Salesman problem Using Branch and Bound
Переглядів 5 тис.4 роки тому
This video is about Travelling Salesman problem Using Branch and Bound. If you are interested in building cool Natural Language Processing (NLP) Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us at info@firstlanguage.in
Randomized Quick Sort
Переглядів 22 тис.4 роки тому
This video is about Randomized quick sort algorithm. If you are interested in building cool Natural Language Processing Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us at info@firstlanguage.in
Rabin Karp Pattern Matching Algorithm
Переглядів 21 тис.4 роки тому
This algorithm is about Rabin Karp Pattern Matching Algorithm. If you are interested in building cool Natural Language Processing Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us at info@firstlanguage.in
Introduction to How Google Search Works , How Information Retrieval System works
Переглядів 1,2 тис.4 роки тому
This video is an Introduction to How Google Search Works , How Information Retrieval System works. If you are interested in building cool Natural Language Processing (NLP) Apps , access our NLP APIs at www.firstlanguage.in/ . Also for NLP product development and consultation, please reach out to us at info@firstlanguage.in
Coreference Resolution
Переглядів 15 тис.4 роки тому
Coreference Resolution
Word Sense Disambiguation Using Naive bayes Classifier
Переглядів 4,7 тис.4 роки тому
Word Sense Disambiguation Using Naive bayes Classifier
Text Coherence
Переглядів 2,1 тис.4 роки тому
Text Coherence
Representation of Semantics Using First Order Logic
Переглядів 1,4 тис.4 роки тому
Representation of Semantics Using First Order Logic
Word Embedding- Meaning Representation of Text
Переглядів 1,1 тис.4 роки тому
Word Embedding- Meaning Representation of Text
Introduction On Semantics
Переглядів 1,1 тис.4 роки тому
Introduction On Semantics
Lecture 22- K Nearest Neighbor (KNN) Algorithm
Переглядів 39 тис.4 роки тому
Lecture 22- K Nearest Neighbor (KNN) Algorithm
Lecture 21-Bayesian Belief Networks using Solved Example
Переглядів 114 тис.5 років тому
Lecture 21-Bayesian Belief Networks using Solved Example
Lecture 20- Linear Discriminant Analysis ( LDA) (with Solved Example)
Переглядів 172 тис.5 років тому
Lecture 20- Linear Discriminant Analysis ( LDA) (with Solved Example)
Lecture 19-DBSCAN Clustering
Переглядів 8 тис.5 років тому
Lecture 19-DBSCAN Clustering
Lecture 18-Random Forest Algorithm
Переглядів 17 тис.5 років тому
Lecture 18-Random Forest Algorithm
Lecture 17- Rand index Calculation
Переглядів 15 тис.5 років тому
Lecture 17- Rand index Calculation
Lecture 16- Eigen Vector Calculation for a Given Matrix
Переглядів 3,3 тис.5 років тому
Lecture 16- Eigen Vector Calculation for a Given Matrix
Lecture 15-Bayesian Hierarchical Clustering
Переглядів 3,1 тис.5 років тому
Lecture 15-Bayesian Hierarchical Clustering
Lecture 14-Hierarchical Agglomerative Clustering (HAC)
Переглядів 16 тис.5 років тому
Lecture 14-Hierarchical Agglomerative Clustering (HAC)
Lecture 13-Naive Bayes Classifier (Audio and Video Sync Fixed Version)
Переглядів 1,8 тис.5 років тому
Lecture 13-Naive Bayes Classifier (Audio and Video Sync Fixed Version)
Naive Bayes classifier
Переглядів 23 тис.5 років тому
Naive Bayes classifier

КОМЕНТАРІ

  • @ganeshmula4508
    @ganeshmula4508 Місяць тому

    wow... great video🙌🙌

  • @sarigamapadhanisa5167
    @sarigamapadhanisa5167 Місяць тому

    covarience 1/n or 1/(n-1)

    • @jhsyesu
      @jhsyesu Місяць тому

      Same doubt

  • @thirumurugankumaresan4631
    @thirumurugankumaresan4631 Місяць тому

    how to find eigen values for 7x7 matrix

  • @sameerdev1
    @sameerdev1 5 місяців тому

    All videos I see are similar but nobody is explaining with a proper numeric example

  • @shenzhouzhang7430
    @shenzhouzhang7430 5 місяців тому

    Hi thank you for your video it explained everything in small detail, i just wonder, when we do the policy evaluation should we take the best action for example when north is 1.8 and south is 1.2 we should do 0 + 1.8 instead of 0 +1.8 + 1.2, i assume this is what max mean in the v funvtion, thanks

  • @RanjithRanjith-ez9le
    @RanjithRanjith-ez9le 5 місяців тому

    From where did you take these notes mam??

  • @santosh.s9556
    @santosh.s9556 6 місяців тому

    😢😢 hereafter ,try to explain without lagging in speech please. I can't able to understand anything

  • @parthpatwari3174
    @parthpatwari3174 7 місяців тому

    You deserve more

  • @parthpatwari3174
    @parthpatwari3174 7 місяців тому

    7:35 how did you made that matrix? I don't get it 😭, can someone plz explain quickly, I have exam tomorrow 😱😱

  • @Chegg.learndim
    @Chegg.learndim 7 місяців тому

    Can we write for Data Mining

  • @HamzaKhan-tu6xl
    @HamzaKhan-tu6xl 7 місяців тому

    Jhant padhai hai

  • @Jaishreerammodijiom
    @Jaishreerammodijiom 8 місяців тому

    focker explain clearly

  • @ManveenKaurMann
    @ManveenKaurMann 8 місяців тому

    b) Calculate Probability of work holiday and wet grass, if no wind, not cloudy, but rain. please provide answer for this

  • @chakrawutsuwannacharoen7030
    @chakrawutsuwannacharoen7030 8 місяців тому

    how to calculate the Martix graph?

  • @SabariMuruganSivakumar
    @SabariMuruganSivakumar 8 місяців тому

    P(Not Rain) can be computed easily as 1 - P (Rain)

  • @murugeswarig3386
    @murugeswarig3386 10 місяців тому

    Really wonderful! Thank you 🙏

  • @Choudhary2003jaat
    @Choudhary2003jaat 11 місяців тому

    Best explanation mam❤

  • @adrenochromeaddict4232
    @adrenochromeaddict4232 Рік тому

    in S_1 2.6 should be 2.64

  • @abhijitmanna4524
    @abhijitmanna4524 Рік тому

    maam we can directly calculate the probability of not rain by subtracting 1-P(rain)

  • @SKStation10
    @SKStation10 Рік тому

    Why your Sw^-1 is different in the final formula and computation?

  • @omsankhe19
    @omsankhe19 Рік тому

    There is absolutely no explanation in this video. This madam here has basically copied a solution from textbook and showed zero solving wasted my 30 min understanding this 13 min video. On top of it in the LDA video, she has asked to watch this video to understand eigen vectors and eigen values.

  • @UtkarshaSalve-u5s
    @UtkarshaSalve-u5s Рік тому

    Helpful ❤❤

  • @rahulss3063
    @rahulss3063 Рік тому

    mam you have amistake in inverse formula

  • @pratikerande4808
    @pratikerande4808 Рік тому

    nice and concise explanation, thanks for sharing

  • @vinayak1998th
    @vinayak1998th Рік тому

    Stumbled upon this video, felt nice to learn from Ma'am after so long

  • @RajeshKamineni4269
    @RajeshKamineni4269 Рік тому

    Best explanation with numbers instead of just formulas and math. First we need to understand conceptually before we work on forumlas

  • @pass_i0ngupta295
    @pass_i0ngupta295 Рік тому

    Guys do check this video, If you are looking for a good machine learning series with basics to advanced topics covered. ua-cam.com/video/YLSuxw_mLIE/v-deo.html

  • @mithunshaha4342
    @mithunshaha4342 Рік тому

    very Nice Explanation,Mam.Needs More tutorial From You.

  • @dheerajkumarsiripalli9363

    Thanks for such a nice explanation mam ❤ saved my phone exam prep tonight

  • @saipriya-jg8tv
    @saipriya-jg8tv Рік тому

    Low voice

  • @PalanisamyPalanisamy-g3d
    @PalanisamyPalanisamy-g3d Рік тому

    super explanation maam....

  • @adithyak1785
    @adithyak1785 Рік тому

    Why square is using?

  • @gulabpreetsingh9985
    @gulabpreetsingh9985 Рік тому

    Hello Maam, at 9:17 HOW you calculated the value [-0.91 -0.39] ^T. would you elobrate this maam

  • @dkkektmsnsndm2084
    @dkkektmsnsndm2084 Рік тому

    Very good explanation mam. Love from Türkiye <3

  • @vijayreddy3423
    @vijayreddy3423 Рік тому

    Really good vedio

  • @vigneshdayalan5804
    @vigneshdayalan5804 Рік тому

    It understood in an easiest way

  • @020hamza2
    @020hamza2 Рік тому

    Couldn't understand

  • @anushkachauhan6428
    @anushkachauhan6428 Рік тому

    Thank you so much for this amazing and clear explanation!

  • @senthilkumaravel8305
    @senthilkumaravel8305 Рік тому

    Thank you, Madam. I solved the following problem. X = [20, 25, 30, 35] Y = [625, 730, 850, 1075] Sum of x = 110 and mean of x is 27.5 Sum of y = 3280 and mean of y is 820 Sum of (x - Mean of x) pow 2 is 125 Sum of (x - Mean of x) × Sum of (y- Mean of y) is 3675 B0 is 99.7 B1 is 29.4 Sum of (cap y - y) pow is 2 Getting standard error of estimate is 93.70 Is my SE estimation correct?

  • @masterleague8349
    @masterleague8349 Рік тому

    At 7:00 , the ų1-ų2 is incorrect, it should be [-5.4 1]

  • @bhuvaneshwarikenny9842
    @bhuvaneshwarikenny9842 Рік тому

    Neka poturuka answer tha podanum illa athu thappa please tell akka

  • @bhuvaneshwarikenny9842
    @bhuvaneshwarikenny9842 Рік тому

    Values multiple pane patha vera answer varuthu akka

  • @Manishkumar-mw2zw
    @Manishkumar-mw2zw Рік тому

    amazing explanation

  • @zaidnadeem4918
    @zaidnadeem4918 Рік тому

    May ALLAH bless you

  • @zaidnadeem4918
    @zaidnadeem4918 Рік тому

    Mam I am doing project on anaphora resolution. I find your video very helpful and informative.

  • @biswajeetraut9178
    @biswajeetraut9178 Рік тому

  • @Surya-np1bb
    @Surya-np1bb Рік тому

    Thank you so much mam, it was very helpful.

  • @ShubhangiKrishnan
    @ShubhangiKrishnan Рік тому

    Can you please link a PDF of your notes in this video?

  • @somiad7878
    @somiad7878 Рік тому

    Great video, thanks!

  • @PrajaktaKharwandikar
    @PrajaktaKharwandikar Рік тому

    best lectures on ML Thank u so much maam for u r efforts