Another treat! Early access to Intro To Machine Learning videos


(Sumit) #706

@sashankpappu

Have you tried restarting the notebook and run the code

again !!

Sumit


(Erick Giffoni) #707

Hi, people. Can someone help me on lesson 2 ? [Workbook 1]

I got this when running : 

Captura de Tela 2018-07-13 às 12.16.17


(Erick Giffoni) #708

and

Captura de Tela 2018-07-13 às 12.16.36


(Sumit) #709

@Erick_Giffoni

Please run this conda install -c anaconda graphviz .
Let me know if it doesn’t work.


(Sumit) #710

@Jdemlow

I’m facing the same issue but couldn’t able to solve it.
After looking into forums i ran this conda install -c defaults intel-openmp -f but nothing happend & also i don’t know what’s the significance of it.

Have you solved it? Can you please help me.

Thanks,
Sumit


(sashank) #711

yes , its the same … I later realized that feature logic is not working in my system now sure why .


(Sumit) #712

Can you tell what’s the shape of df and y?
& what’s showing after you run proc_df , I mean any error or anything which will be helpful to figure what’s wrong ?

and also if at all df & y has values then can you post first 4-5 rows in here .

Thanks,
Sumit


(Erick Giffoni) #713

Thank you. It worked.


(Aditya) #714

Check your mem


(Aditya) #715

This is amazing!!


(Sumit) #716

can anyone please help me.

Thanks,
Sumit


#717

Hi Jeremy since these videos are not to be found on courses.fast.ai and only on youtube am I right in presuming that they have not been formally launched as of yet for the ML course


(Yoong Kang Lim) #718

Hey everyone! First post here.

In the video for lesson 7, about 18 minutes in @jeremy makes a point about imbalanced datasets. He mentioned a recent paper that looked at some approaches to deal with this and concluded that oversampling from the smaller category wins out consistently.

Has anyone tracked down this paper? I’d love to have a look at it.


(sashank) #719

When should we use One Hot Encoding & Categorical Codes . Can anyone help me on this ?
For eg : for countries what should we use ?


(Kieran) #720

Use the train_cats() function which takes your data frame and changes the categorical variables to data type (dtype) category. Then when we call proc_df() these categorical variables will be changed to numeric variables. Its important that they all have the same spelling etc!

Check out 7:58 on Machine Learning 1 lesson 2 video.

Hope that helps


(Kieran) #721

My guess is that its one of these on this scholar search.
Problem is they tend to be uber technical and in general you have to pay for them.

https://scholar.google.ca/scholar?hl=en&as_sdt=0%2C5&as_ylo=2016&as_vis=1&q=training+with+imbalanced+data+set+oversampling&btnG=

Let me know if you find anything interesting :slight_smile:


#722

Hey, I’m also facing the very same issue. My kernel gets restarted when trying to run df, y, nas = proc_df(df_raw, ‘SalePrice’). This issue is seen with a dataframe size of 100. Where you able to resolve this issue?


(Sanyam Bhutani) #723

Cross Posting here for visibility:

I’ll host weekly discussions starting on the 12th of August. (ML MOOC)

Please take a second to vote for timings if you’re interested .

Sanyam


#724

Additionally to those, I had to install:

  • pip install isoweek
  • pip install pandas-summary

To find out which dependencies you might be lacking, it is useful to start an interactive python session just by typing “python” on the command line prompt and then running
from fastai.imports import *
at the python “>>>” prompt until you get no errors. Any errors there should show the missing dependencies.


(Axel Straminsky) #725

In one of the lectures Jeremy showed a library for interpreting random forests, but if I remember correctly he said that he didn’t know of a library that did the same for Neural Nets. A few days ago I came across a new library called SHAP, that apparently is not only for interpreting RF, but any ML model. Has anyone tried it?

Repo: https://github.com/slundberg/shap