Easy ML
Easy ML
  • Видео 93
  • Просмотров 455 292
Introduction to Iris Data
Introduction to Iris Data
Просмотров: 6 061

Видео

Data Normalization using Z-Score technique
Просмотров 20 тыс.5 лет назад
Data Normalization using Z-Score technique
Data Visualization
Просмотров 2,8 тыс.5 лет назад
Data Visualization
Introduction to R Studio - Part 1
Просмотров 1,1 тыс.5 лет назад
Introduction to R Studio - Part 1
Introduction to R Studio - Part 2
Просмотров 1 тыс.5 лет назад
Introduction to R Studio - Part 2
Introduction to Supervised Learning
Просмотров 2,2 тыс.5 лет назад
Introduction to Supervised Learning
Introduction to Correlation Coefficients
Просмотров 2,5 тыс.5 лет назад
Introduction to Correlation Coefficients
Introduction to Correlation Matrix
Просмотров 50 тыс.5 лет назад
Introduction to Correlation Matrix
Evaluating accuracy of Regression Models
Просмотров 17 тыс.5 лет назад
Evaluating accuracy of Regression Models
Evaluating efficiency of Regression Models
Просмотров 1,6 тыс.5 лет назад
Evaluating efficiency of Regression Models
Building Regression Models
Просмотров 6 тыс.5 лет назад
Building Regression Models
Regression Models - Step 2 : Splitting Data
Просмотров 1,5 тыс.5 лет назад
Regression Models - Step 2 : Splitting Data
Regression Models - Introduction to Correlation
Просмотров 1,5 тыс.5 лет назад
Regression Models - Introduction to Correlation
Regression Models - Step 1 : Variable Selection (Part 1)
Просмотров 2,3 тыс.5 лет назад
Regression Models - Step 1 : Variable Selection (Part 1)
Regression Models - Step 1 : Variable Selection (Part 2)
Просмотров 1,7 тыс.5 лет назад
Regression Models - Step 1 : Variable Selection (Part 2)
Spurious Correlations - Why we need Regression Models ?
Просмотров 4,1 тыс.5 лет назад
Spurious Correlations - Why we need Regression Models ?
Introduction to types of Correlation
Просмотров 1,8 тыс.5 лет назад
Introduction to types of Correlation
Building Random Forest Models
Просмотров 1,4 тыс.5 лет назад
Building Random Forest Models
Evaluating Random Forest Models
Просмотров 1,7 тыс.5 лет назад
Evaluating Random Forest Models
Introduction to Random Forest Models - Understanding Decision Trees (Part 1)
Просмотров 1,3 тыс.5 лет назад
Introduction to Random Forest Models - Understanding Decision Trees (Part 1)
Random Forest Model - Iris Data
Просмотров 2 тыс.5 лет назад
Random Forest Model - Iris Data
Understanding Decision Trees (Part 2)
Просмотров 7055 лет назад
Understanding Decision Trees (Part 2)
Introduction to Unsupervised Learning
Просмотров 2 тыс.5 лет назад
Introduction to Unsupervised Learning
Evaluating K-Means Cluster Analysis
Просмотров 8 тыс.5 лет назад
Evaluating K-Means Cluster Analysis
Introduction to Cluster Analysis
Просмотров 1,9 тыс.5 лет назад
Introduction to Cluster Analysis
Introduction to K-means - Choosing number of clusters
Просмотров 16 тыс.5 лет назад
Introduction to K-means - Choosing number of clusters
K-Means Clustering - Iterations
Просмотров 4,8 тыс.5 лет назад
K-Means Clustering - Iterations
Evaluating Principal Component Analysis (PCA) - Part 1
Просмотров 1,2 тыс.5 лет назад
Evaluating Principal Component Analysis (PCA) - Part 1
Evaluating Principal Component Analysis (PCA) - Part 2
Просмотров 1 тыс.5 лет назад
Evaluating Principal Component Analysis (PCA) - Part 2
Introduction to Principal Component Analysis (PCA)
Просмотров 1,8 тыс.5 лет назад
Introduction to Principal Component Analysis (PCA)

Комментарии

  • @TheUmaragu
    @TheUmaragu 6 дней назад

    Nice explanation; I loved the way you used the two extreme cases for clustering.

  • @ldsharma6546
    @ldsharma6546 9 дней назад

    Sir, I have analysed 850 soil samples for different forms of soil acidity and 7 other soil properties like pH, EC, OC etc. Sir, I would like to predict Exchangeable acidity (numeric) with 7 soil parameters. How should I calculate random forest?

  • @tmitra001
    @tmitra001 26 дней назад

    what is nc in WSS function?

    • @tmitra001
      @tmitra001 26 дней назад

      Ok I got what is nc!!

  • @hauntedmonk3382
    @hauntedmonk3382 27 дней назад

    Thank you ur vedio brought me a hope that R is easy

  • @Vesna_Covic
    @Vesna_Covic 2 месяца назад

    why the f you scream this much...

  • @Swormy097
    @Swormy097 2 месяца назад

    Thank you so much❤

  • @aneeshkumarkv7792
    @aneeshkumarkv7792 2 месяца назад

    Made it so simple and illustrative... thanks a lot

  • @kevinshao9148
    @kevinshao9148 3 месяца назад

    Hi, what is this "predict(...)" function? Is it from 'randomForest" or it's R built-in function? Thanks

  • @mehrananjum5501
    @mehrananjum5501 4 месяца назад

    Hello, Can you help me please

  • @expeditadjovi9927
    @expeditadjovi9927 5 месяцев назад

    good explanation

  • @heznadastudios
    @heznadastudios 5 месяцев назад

    What if i'm trying to load my personal data in?

  • @gauravdeshmukh9451
    @gauravdeshmukh9451 5 месяцев назад

    can you please make this same video but in python...

  • @emirhandemir3872
    @emirhandemir3872 6 месяцев назад

    My autoplot(KM, mydata, frame= TRUE) doesn't work. I run it and it doesn't do anything. I have to point out that I didn't run the wssplot function though. Is it because of that? I fixed it. It's because of my lack of R syntax knowledge! I have no idea why but I am running R in vscode and vscode doesn't print the variables if they are not in a print function.

  • @ibrahimnahushal9353
    @ibrahimnahushal9353 7 месяцев назад

    good job, short and directly to the point. thank you

  • @taisepinheiro8747
    @taisepinheiro8747 7 месяцев назад

    Hi, thank you very much for sharing this video :) the only one tutorial that I was able to follow. One question, my predicted variable is not categorial, but it´s an area of deforestation. So, Can I use the code you shared in this video?

  • @noble7578
    @noble7578 7 месяцев назад

    Excellent explanation! Thank you!

  • @prachimehta8634
    @prachimehta8634 8 месяцев назад

    So glad to see 85k views!

  • @estrellitalinda7658
    @estrellitalinda7658 8 месяцев назад

    how can incorporate upsamling or downsampling before running the random forest model? neeeeed help pls

  • @marshmellowmash
    @marshmellowmash 8 месяцев назад

    This whole series was so helpful - thank you so much!

  • @michaelogunmakin9143
    @michaelogunmakin9143 9 месяцев назад

    Super helpful, thanks!

  • @Aloneincrowd3
    @Aloneincrowd3 9 месяцев назад

    The mean of my cor(data) is 0.45. Is it not eligible for pca? What should i use for variable selection then?

  • @mikemartinez5970
    @mikemartinez5970 9 месяцев назад

    Excellent video!! Thank you so much

  • @prachimehta8634
    @prachimehta8634 10 месяцев назад

    29k views! 👏

  • @jakubosobka4414
    @jakubosobka4414 10 месяцев назад

    Worst educational video I've seen for a while. And I've watch thousands.

  • @FrOsTyBeArKiD
    @FrOsTyBeArKiD 11 месяцев назад

    This was very very clear. I enjoy the examples showing the extreme scenarios to make the optimum example hit home.

  • @halilzelenka5813
    @halilzelenka5813 11 месяцев назад

    Hansel is a thicc boy

  • @nehachaudhuri8475
    @nehachaudhuri8475 11 месяцев назад

    You have some great videos. Why have you stopped posting videos?

  • @BhavaniSc
    @BhavaniSc 11 месяцев назад

    This was so helpful thank you

  • @codecrafts5263
    @codecrafts5263 Год назад

    After 2 hrs of surfing internet about the subject, i found this video and it clarified the concept in 3.11 minutes. Really Thank you

  • @oshadeegunawardhana388
    @oshadeegunawardhana388 Год назад

    Nice explaination ❤

  • @halagundegowdagr2877
    @halagundegowdagr2877 Год назад

    Sir, You are a Good TEACHER, Short and sweet explanation, Superb

  • @Think0Like0Cheese
    @Think0Like0Cheese Год назад

    us data analysts learning more than necessary about plant terminology..

  • @ofirshorshy8281
    @ofirshorshy8281 Год назад

    useful. thank you. I will try this.

  • @elifceyhan78
    @elifceyhan78 Год назад

    Hello, thanks for great video! It is heelpful. What do you suggest for stability test in r? Which function I can use?

  • @muh.anugrahpratama1752
    @muh.anugrahpratama1752 Год назад

    Bang kalau pake data citra data raster bisa nggak?

  • @alinaastakhova8412
    @alinaastakhova8412 Год назад

    Thank You very-very much! It is certainly one of the best explanations. Very helpful! But I have got some questions. 1) I can not understand what do we do next with the PCAs? Shall I use it for multiple regression along with other variables or for clustering? 2) Can I reevaluate impact of variables using loading data? For instance, I use 5 variables to build PCAs. My PCA1 and 2 describe about 85% of variability, but each PCA does not connect to - lets say - the 3rd variable. May be I should delete the 3rd variable and run the analysis with only 4 others? Will this improve the outcome? 3) Why are some spaces blank in loadings (minute 6.28 on the video) - like Sepal.Width vs Comp.1? 4) And the final - body mass index is given as an example of PCA outcome. Does that mean that we can retrieve PCA1 and name it as a sort of new stable variable? Or BMI is just an example of data dimension reduction that does not correspond to PCA directly? Thats a lot of questions - but I really wonder...

    • @easyml1234
      @easyml1234 Год назад

      Hey thank you for such a detailed comment. At times I wish RUclips allows voice notes because typing would be ineffective per se. BMI is indeed just an example. The main application of PCA is to capture the essence of a large list of variables in fewer newly generated variables. Assume you have bank data.. there is a list of 120 variables and you need to predict loan delinquency. Inputting 120 variables and eventually tuning the model would be cumbersome in such instances you can deploy PCA to reduce the list of variables from 120 to let us say 12 and rest assured if you have executed PCA well then these 12 variables would have correctly captured the essence of the original 120 variables. The model that you will be building with these new set of PCs will be lighter and faster. You can deploy PCA before unsupervised learning as well !!

    • @alinaastakhova8412
      @alinaastakhova8412 Год назад

      @@easyml1234 thanks! my point is - may be I don't need all 120. May be, I should extract 40 for one PCA and other 50 for another one and discard the remaining 30 and I will get better sketch of my "Eiffel tower" - that was a great example)) at least, I might get better values of my PC1 and PC2 equations. do we do so? reduce data for several PCAs? And once I get results of several PCAs - how do I interpret them? As variables for regression or basis for clustering?

    • @sutanukadas9049
      @sutanukadas9049 Год назад

      ​@@easyml1234can this method used for categorical data ?

  • @manifestationmaster1111
    @manifestationmaster1111 Год назад

    Thank you man, you finally made it made sense!

    • @easyml1234
      @easyml1234 Год назад

      Thanks a lot for your comment Like / Share and Subscribe 🙏

  • @umermuhammad826
    @umermuhammad826 Год назад

    Hello EasyML Awesome tutorial video. I wanted to know how can we determine the individual components of a cluster? What each of these blue and orange dots represents on the autoplot? Please help. Thanks in advance.

  • @robtaylor2781
    @robtaylor2781 Год назад

    Thanks very much . Well explained and very useful

  • @AnkitKumar-rx7ky
    @AnkitKumar-rx7ky Год назад

    sir I feel there is some problem with the explanation here of the confusion matrix. The axis needs to be reversed.

    • @easyml1234
      @easyml1234 Год назад

      1:14 - Number of predicted females are 15 and number of Actual Females are also 15 so that is right. I guess the confusion may stem from the fact that there are 3 values or boxes with 15 if I have filled it with different values it would have been easier to follow. The logic is correct but because of the similar numbering there could be some confusion. Anyway thanks for this !

  • @kabberkartuj8924
    @kabberkartuj8924 Год назад

    Very helpful play list. Thanks a lot

  • @zin6487
    @zin6487 Год назад

    Thank Sir

  • @salmaasghar1674
    @salmaasghar1674 Год назад

    EXCELLENT tutorial I must say.... you are born with extraordinary God-gifted abilities my dear.

  • @salmaasghar1674
    @salmaasghar1674 Год назад

    I had to stop the video to appreciate you for such a wonderful tutorial.

  • @easyml1234
    @easyml1234 Год назад

    Full video here :- ruclips.net/video/NfIM9pUH9DA/видео.html

  • @Dipsree
    @Dipsree Год назад

    how do you determine what each cluster represents?

  • @dr.manikdhawan5725
    @dr.manikdhawan5725 Год назад

    mode functions show "numeric" as answer :( help

  • @alexandrsgrind3743
    @alexandrsgrind3743 Год назад

    even if my ears hurt by your hardcore indian accent, your way to explain is brilliant, sir!

  • @djangoworldwide7925
    @djangoworldwide7925 Год назад

    While computing mean correlation you shouldve get rid of the diag and upper trig (?)

  • @amanduskar
    @amanduskar Год назад

    you are a life saver! Thank you for this simple explanation