Lecture 2: Working with Images & Logistic Regression

Session Links
English: https://youtu.be/uuuzvOEC0zw
Hindi: https://youtu.be/qmzgJvVP9XA

Lecture Date and Time: November 28, 2020,
English: 9 PM IST/8.30 AM PST | Add to calendar (Google)
Hindi: 11 AM IST | Add to calendar (Google)

Notebooks :

  1. Logistic Regression: https://jovian.ai/aakashns/03-logistic-regression
  2. Logistic Regression minimal starter: https://jovian.ai/aakashns/mnist-logistic-minimal
  3. Linear Regression minimal starter: https://jovian.ai/aakashns/housing-linear-minimal

What to do after the lecture?

  • Run the Jupyter notebooks shared above (try other datasets)
  • Ask and answer questions on this topic (scroll down)
  • Start working on Assignment 2 - Train Your First Model

Asking/Answering Questions:

Reply on this thread to ask questions during and after the lecture. Before asking, scroll through the thread and check if your question (or a similar one) is already present. If yes, just like it. During the lecture, we’ll answer 8-10 questions with the most likes. The rest will be answered on the forum. If you see a question you know the answer to, please post your answer as a reply to that question. Let’s help each other learn!

too fast for beginner … but that’s ok … I need to refresh maths and revisit session multiple times :slight_smile:

1 Like

Is there a method to choosebatch size?

what are things to note when we do for other image datsets

how to do lebeling for unlabel image datasets

How can we change the learning rate at the point where the model’s accuracy starts becoming constant? Something like adaptive learning rate?

Why during evaluation time we don’t call model.eval() and torch.no_grad?

Helo aakash…
Can I kindly have the recorded video for lecture 2…??

@hemanth, if we want to post our project on linear regression and ask for people’s opinion and advises on it,for this in which group do i post my project?

Thank you for pointing this out, @sathi-satb!
I have created a new thread which can be found here:

Hey @agatha-l, the session links are given in the description above!

as @aakashns was calling fit function for 5 5 epochs, and was printing result of each iteration, from there we can figure out whether our accuracy is getting constant, then we decrease learning rate for next call of fit function.

the kernel dies as soon as i do plt.imshow() in my jupyter notebook