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Commit b93156d

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sample notebook uploaded
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import tensorflow as tf"
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from tensorflow import keras"
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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": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'2.7.0'"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tf.__version__"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'2.7.0'"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"keras.__version__"
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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": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<tf.Tensor: shape=(), dtype=string, numpy=b'Hello World'>"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"hello = tf.constant(\"Hello World\")\n",
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"hello "
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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": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz\n",
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"32768/29515 [=================================] - 0s 1us/step\n",
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"40960/29515 [=========================================] - 0s 1us/step\n",
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"Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz\n",
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"26427392/26421880 [==============================] - 4s 0us/step\n",
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"26435584/26421880 [==============================] - 4s 0us/step\n",
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"Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz\n",
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"16384/5148 [===============================================================================================] - 0s 0s/step\n",
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"Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz\n",
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"4423680/4422102 [==============================] - 1s 0us/step\n",
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"4431872/4422102 [==============================] - 1s 0us/step\n"
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]
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}
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],
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"source": [
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"fashion_mnist = keras.datasets.fashion_mnist\n",
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"(X_train_full, y_train_full),(X_test, y_test) = fashion_mnist.load_data()"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(60000, 28, 28)"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"X_train_full.shape"
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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": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"dtype('uint8')"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"X_train_full.dtype"
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]
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}
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],
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"metadata": {
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"interpreter": {
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"hash": "0989d4cb382ec003e6ad9ee0079fe5a34620af18f47069c43c62ee5030c1ec77"
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},
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"kernelspec": {
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"display_name": "Python 3.7.9 64-bit ('myenv': conda)",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.12"
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},
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"orig_nbformat": 2
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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