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udlbook
2023-07-27 12:05:56 -04:00
parent b6bc481fec
commit 7f4cf1acb7
1 changed files with 2 additions and 2 deletions
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Notebooks/Chap06/6_3_Stochastic_Gradient_Descent.ipynb
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@@ -4,7 +4,7 @@
"metadata": { "metadata": {
"colab": { "colab": {
"provenance": [], "provenance": [],
"authorship_tag": "ABX9TyN/trn2b+dsX0Qcg4ZzNZEf", "authorship_tag": "ABX9TyNk5FN4qlw3pk8BwDVWw1jN",
"include_colab_link": true "include_colab_link": true
}, },
"kernelspec": { "kernelspec": {
@@ -547,7 +547,7 @@
"for c_step in range (n_steps):\n", "for c_step in range (n_steps):\n",
" # Do gradient descent step\n", " # Do gradient descent step\n",
" phi_all[:,c_step+1:c_step+2] = stochastic_gradient_descent_step(phi_all[:,c_step:c_step+1],data, alpha =0.8, batch_size=5)\n", " phi_all[:,c_step+1:c_step+2] = stochastic_gradient_descent_step(phi_all[:,c_step:c_step+1],data, alpha =0.8, batch_size=5)\n",
" # Measure loss and draw model every 4th step\n", " # Measure loss and draw model every 8th step\n",
" if c_step % 8 == 0:\n", " if c_step % 8 == 0:\n",
" loss = compute_loss(data[0,:], data[1,:], model, phi_all[:,c_step+1:c_step+2])\n", " loss = compute_loss(data[0,:], data[1,:], model, phi_all[:,c_step+1:c_step+2])\n",
" draw_model(data,model,phi_all[:,c_step+1], \"Iteration %d, loss = %f\"%(c_step+1,loss))\n", " draw_model(data,model,phi_all[:,c_step+1], \"Iteration %d, loss = %f\"%(c_step+1,loss))\n",