Ok. Thank you for your answer !
Yes it is lecture 1 today in about 23 minutes. Please refer the description of this thread for the attendance poll.Lecture 1 - PyTorch Basics & Linear Regression
I have the same problem… and I did uncomment the line !conda install pytorch cpuonly -c pytorch -y . If anybody has any ideas i wopuld love them… other wise I will setup a Debian enviroment.
Hello there @ PrajwalPrashanth sorry to reply late.
I get this error message when I run the code import torch and the rest of the code. But normal python is able to work
I already marked the attendance will it be okay
I get the error when I am trying to import torch. and I already uncommented the line and it says
Collecting package metadata (current_repodata.json): …working… done
Solving environment: …working… done
All requested packages already installed.
Then when I try to run the next cell:
A humble request do show the steps to install and how to go forward with Jovian into our notebooks.
It will be helpful - thank you!
I also got the same error…now I am using my base conda enviroment…in that I am not getting any error
@PrajwalPrashanth when I try to install the pip jovian it came out an error is “Some pip package fail to install” as the picture below… Is this causing the problem I mention above
When you say you’re running your base conda environment what do you mean? I’m getting the same error as alvertosk84
https://jovian.ml/aakashns/machine-learning-intro This is the first notebook. Don’t worry you if you’re facing issues with installation. You have option to run the notebook on kaggle/colab.
I will update the list if installation instructions later on
Great Session Akash!! Thanks!!
Do we get a confirmation that we have attended the first lecture?
Just finished the lecture 1, have been learning python for over 4 months and now i think data science is what I’m gonna pursue my career on. Thank you so much. Looking forward in practicing right now and learning more.
it was really good session to kick start for all !!! . Thanks Aakash !!!
How mark my
Hey, great lecture but it left me with a couple questions:
- What happens if the weight, by chance, starts at a local maxima? Since the derivative would be zero, which direction would the weight change?
- Can someone clarify what .backward() actually does?
- Is there any “rule of thumb” surrounding epoch amount, training set length, and learning size/step size?
- Why is squared loss used as opposed to the absolute value?
It was an amazing session sir .
thanks a lot for making it free.
- Then you subtract the zero from the weights, so they stays the same.
- It’s to actually calculate the gradients (I think they’re not calculated automatically when performing operations).
- Sometimes you train until your loss stops decreasing (with unspecified amount of epochs). What’s really important is the data - the more the better.
- Just a preference, it could be used as well (it’s called L1 loss or sth in PyTorch).
Finally found the attendance button. lol