Комментарии •

  • @krishnaikhindi
    @krishnaikhindi 2 года назад +7

    Hello Guys,
    Finally iNeuron is happy to announce Full Stack Data Scientist Bootcamp with Job Guarantee Program starting from 7th May 2022 and the class timing is from 10am to 1 pm and then the doubt clearing session is from 1pm to 3pm every Saturday and Sunday. This time we are keeping 2 hours doubt clearing session after the class.
    All the live sessions will be recorded and it will be available through lifetime.Even prerecorded videos are also available for everyone.
    You can check the detailed syllabus and all information below
    courses.ineuron.ai/Full-Stack-Data-Science-Bootcamp
    Use Krish10 for additional 10% discount
    Emi options also available
    Direct call to our Team incase of any queries
    8788503778
    6260726925
    9538303385
    8660034247
    9880055539

    • @ssensation
      @ssensation Год назад +1

      Sir I love to take your course but I am working professional it very hard to follow
      Sir your Hindi playlist is one of the best

    • @SthitadhiDas
      @SthitadhiDas 4 месяца назад

      liked your presentation👌👌👌👌

  • @MuzammilRazaBCSFBM
    @MuzammilRazaBCSFBM Год назад +16

    Thumbnail be like: nikal ❤️day . 😁

  • @avishekbasyal2582
    @avishekbasyal2582 4 месяца назад

    Where the practical implementation of Naive Bayes algorithm?

  • @shashijaiswal5921
    @shashijaiswal5921 Месяц назад

    how the graph is plotted for 3 feature. like size, room and price????

  • @Rocky_67890
    @Rocky_67890 Месяц назад

    Is this playlist sufficient to crack online tests and interview? @krishnaikhindi

  • @krishnabhutada3983
    @krishnabhutada3983 2 года назад +4

    Please start Deep learning 7 days live session at the earliest.

  • @akashsoni5870
    @akashsoni5870 2 года назад +2

    Please start deep learning and computer vision 7 days lecture

  • @ankitpathak4863
    @ankitpathak4863 2 года назад +4

    Sir, what happens when 1's and 0's have the same number of data points under KNN i.e. 3 for 1's and 3 for 0's, Then what would be the output?

    • @h44r96
      @h44r96 Год назад +2

      This understanding comes with practical knowledge or domain knowledge. Odd no. of K value is taken into account in that case. K = 3, K = 5

    • @lakshsinghania
      @lakshsinghania Год назад

      same doubt

    • @lakshsinghania
      @lakshsinghania Год назад

      @@h44r96 i did not get this
      u can pls elaborate on ur answer

  • @shibu4513
    @shibu4513 Год назад +1

    Sir
    Where is implementation part? -,-

  • @sauravsahay8803
    @sauravsahay8803 5 месяцев назад

    Can someone share me the python implementation of this video

  • @DivyamPadole
    @DivyamPadole Год назад +1

    Noice

  • @ajiteshsarangi9006
    @ajiteshsarangi9006 Год назад +1

    Please update the material link as this link is showing 404 error

  • @jdjdejei-ok1qt
    @jdjdejei-ok1qt Год назад +1

    sir u didn't uploaded practical implementation of knn.

  • @niluthonte45
    @niluthonte45 Год назад +2

    Thank you sir clearly understood
    🙂

  • @bilalhassankhan221
    @bilalhassankhan221 2 года назад +2

    Please upload same playlist as you uploaded on your second channel. And also, tell us how to follow your playlist.

  • @mdmusaddique_cse7458
    @mdmusaddique_cse7458 Год назад +3

    It was super simplified. Understood well

  • @saajanrajak3054
    @saajanrajak3054 3 месяца назад

    Thanks for showing the visualization for KNN method.
    Have a request, can you share similar examples when input variables 3 or more.
    Thanks again
    @krishnaikhindi

  • @mmbytes1911
    @mmbytes1911 Год назад +1

    Nice way of explaining as well presentation. Can you share what are the gadgets you are using for writing, please 🙏

  • @LouisDuran
    @LouisDuran 7 месяцев назад

    I couldn't understand...

  • @netviz8673
    @netviz8673 Месяц назад

    in classfication problem statement and regression problem statement both me can be uses. Euclidean distance and Manhattan distance.
    In regression, it is the average of the K(hyperparameter) nearest data points whereas in classification problem it is equal to max number of category points out of the K nearest neighbours.
    Limitations:
    Huge dataset me problem create karega.
    Sensitive to Outliers
    Sensitive to missing values

  • @poojaverma3247
    @poojaverma3247 Год назад +1

    🎉🎉🎉🎉🎉🎉🎉

  • @mjunaidmjunaid566
    @mjunaidmjunaid566 2 года назад +2

    Thank you sir ❤😘❤

  • @arhamqamar7462
    @arhamqamar7462 2 года назад +2

    Thanks a lot ❤

  • @AbdullahAlmaharmeh-u8k
    @AbdullahAlmaharmeh-u8k Год назад +1

    can i find English version of this ?

  • @Coden69
    @Coden69 2 года назад +2

    Thanks

  • @rupeshingle217
    @rupeshingle217 Год назад +1

    Best explanation in simple way on RUclips... Great work Krish sir, your Hindi & English both channels are awesome. 👏🙌

  • @soumyabrata111
    @soumyabrata111 Год назад +1

    Lovely

  • @jyothi26rab
    @jyothi26rab 8 месяцев назад

    sier regarding Knn If there are more than 2 classification like 0 1 2 3 4 does THE SAME PRINCIPAL APPLY

  • @tashiaisha3866
    @tashiaisha3866 Год назад +1

    thank you so much! Very helpful

  • @jyothi26rab
    @jyothi26rab 8 месяцев назад

    Sir I have joined ur programe I did not like the teaching method in the live class. I have stopped joining the class i watch all ur vedios on u tube and thats how i learn I cant wait to join ur live class

  • @AnmolSharma-ij1ut
    @AnmolSharma-ij1ut 8 месяцев назад

    but sir how to find the value of k in our problem as the value of k changes the output result will change.

  • @arkarts505
    @arkarts505 Год назад +1

    Thankyou So Much Sir!!!

  • @komalanhad7966
    @komalanhad7966 Год назад +1

    Thank You so much!

  • @zobiakhatoon4959
    @zobiakhatoon4959 10 месяцев назад

    Hello Dear Sir, How can I get your contact details?

  • @malikkashifsaeed5381
    @malikkashifsaeed5381 Год назад +1

    Best explanation with clear and concise way

  • @SurajKumar-dq8ew
    @SurajKumar-dq8ew 11 месяцев назад

    I have a question.
    In classifier, if the value of both the category is same then what will we select. For example if number of 1s are 4 and number of 0s are also 4 then which value will be predicted

  • @pkumar0212
    @pkumar0212 3 месяца назад

    👌

  • @Pr3kashSingh
    @Pr3kashSingh 11 месяцев назад

    Thank you very much sir.

  • @Pankaj_Khanal_Joshi
    @Pankaj_Khanal_Joshi 9 месяцев назад

    Can test data come as outlier

  • @krishj8011
    @krishj8011 4 месяца назад

    Great tutorial...

  • @AnaghaVaidya-c9p
    @AnaghaVaidya-c9p Год назад

    great explanation