Build a Neural Network with Python Tutorial | Deep Learning with PyTorch

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Build a model that predicts whether or not is going to rain tomorrow using real-world weather data. Learn how to train, evaluate and make predictions with it

⭐️ Tutorial Contents ⭐️

(00:12) Download the weather data
(04:13) Data preprocessing
(17:45) Build a Neural Network with PyTorch
(32:05) Choose a loss function & optimizer
(40:25) Doing computations on the GPU (with CUDA)
(44:03) Training your Neural Network
(49:17) Saving & loading a model with PyTorch
(50:15) Evaluation (How good your model is?)
(54:41) Making predictions (Is it going to rain?)

  1. Venelin Valkov
  2. Machine Learning
  3. TensorFlow.js
  4. Artificial Intelligence
  5. Data Science
  6. Deep Learning
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Комментарии
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This guy is awesome, all his tutorials are so easy to follow and are really informative.

benjaminbenjamin
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hello sir, I am your new student i will be visiting your channel every few hours every day. Thank you for teaching me so many things. you are my teacher and am your student now. Thanks again :)

hussain
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I balanced the dataset by oversampling. The best model has forecast rain with 74% accuracy and no rain with 73% accuracy. I've tried different numbers of neurons/nodes in the hidden layer. Next, I will add more hidden layers. I suspect that will have a real impact.

lakeguy
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Thank you very much for this video! Just one question, what happened on 47:35?

forvm
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Are you going to release your modified ANN Visualizer?

cwill
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I have followed your code. What does it mean when the model fails to learn? The train_loss.item() doesn't change after each loop? The NN runs with no errors but doesn't learn. Any ideas? thank you.

lakeguy
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how many cuda cores does the google colab employ? Is there a limit to how big a model you can pass to a colab GPU?

lakeguy
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Superb.... Keep it up..
I need code for this lesson....

rushikeshbulbule
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I don't understand why you didn't balance the dataset since 78% of your y values are zero...

lakeguy