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dcavardcavar
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added new notebooks
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‎notebooks/Multilayer_Perceptron.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Multilayer Perceptron (MLP)\n",
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"\n",
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"© 2024 by [Damir Cavar](http://damir.cavar.me/)\n",
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"\n",
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"\n",
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"**Download:** This and various other Jupyter notebooks are available from my [GitHub repo](https://github.com/dcavar/python-tutorial-for-ipython).\n",
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"\n",
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"**License:** [Creative Commons Attribution-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-sa/4.0/) ([CA BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/))\n",
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"\n",
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"**Literature:**\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Introduction"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Inference"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Training"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**© 2024 by [Damir Cavar](http://damir.cavar.me/)**"
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]
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

‎notebooks/Perceptron Learning in Python.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**(C) 2017-2024 by [Damir Cavar](http://damir.cavar.me/)**"
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"**© 2017-2024 by [Damir Cavar](http://damir.cavar.me/)**"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**(C) 2017-2024 by [Damir Cavar](http://damir.cavar.me/)**"
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"**© 2017-2024 by [Damir Cavar](http://damir.cavar.me/)**"
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]
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}
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‎notebooks/Process_IAB_Taxonomies.ipynb

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{

‎notebooks/Transformers_example_simple_text_classification.ipynb

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"name": "stderr",
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"c:\\Users\\damir\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\transformers\\utils\\generic.py:441: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
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" _torch_pytree._register_pytree_node(\n",
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"c:\\Users\\damir\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\transformers\\utils\\generic.py:309: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
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" _torch_pytree._register_pytree_node(\n"
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"2024-10-23 17:10:52.468340: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
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"2024-10-23 17:10:52.477833: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
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"2024-10-23 17:10:52.489025: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
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"2024-10-23 17:10:52.492373: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
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"2024-10-23 17:10:52.501195: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
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"To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
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"2024-10-23 17:10:53.195914: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
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"execution_count": 2,
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"base_uri": "https://localhost:8080/",
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"outputId": "f3e446e7-4b14-4188-8535-7ae8be01324c"
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "d7d58c4562e24b30b170d3391c018e1e",
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"version_major": 2,
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"version_minor": 0
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"metadata": {},
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"data": {
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"model_id": "e7eb51f52fa34f9ea364e5629dcfed90",
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"model_id": "58b91f0e42d641e4ade231d6601ba465",
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"c:\\Users\\damir\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\huggingface_hub\\file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
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"/home/damir/.local/lib/python3.12/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
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" warnings.warn(\n",
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"Hardware accelerator e.g. GPU is available in the environment, but no `device` argument is passed to the `Pipeline` object. Model will be on CPU.\n"
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"{'sequence': 'We like to use Code for Python, but vim for C.',\n",
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" 'labels': ['programming', 'economy', 'automotive', 'politics'],\n",
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" 'scores': [0.894223690032959,\n",
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" 0.07695318013429642,\n",
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" 0.00736920116469264]}"
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" 'scores': [0.8942243456840515,\n",
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" 0.07695267349481583,\n",
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" 0.021453848108649254,\n",
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" 0.0073691364377737045]}"
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"version": "3.12.7"
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