forked from filipg/aitech-eks-pub
709 lines
22 KiB
Plaintext
709 lines
22 KiB
Plaintext
{
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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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"# Zajecia 2\n",
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"\n",
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"Przydatne materiały:\n",
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"\n",
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"https://scikit-learn.org/0.19/datasets/twenty_newsgroups.html\n",
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"\n",
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"https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html\n",
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"\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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"## Importy"
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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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"import numpy as np\n",
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"import sklearn.metrics\n",
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"\n",
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"from sklearn.datasets import fetch_20newsgroups\n",
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"\n",
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"from sklearn.feature_extraction.text import TfidfVectorizer"
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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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"## Zbiór danych"
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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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"newsgroups = fetch_20newsgroups()['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": 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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"11314"
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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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"len(newsgroups)"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"From: lerxst@wam.umd.edu (where's my thing)\n",
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"Subject: WHAT car is this!?\n",
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"Nntp-Posting-Host: rac3.wam.umd.edu\n",
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"Organization: University of Maryland, College Park\n",
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"Lines: 15\n",
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"\n",
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" I was wondering if anyone out there could enlighten me on this car I saw\n",
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"the other day. It was a 2-door sports car, looked to be from the late 60s/\n",
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"early 70s. It was called a Bricklin. The doors were really small. In addition,\n",
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"the front bumper was separate from the rest of the body. This is \n",
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"all I know. If anyone can tellme a model name, engine specs, years\n",
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"of production, where this car is made, history, or whatever info you\n",
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"have on this funky looking car, please e-mail.\n",
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"\n",
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"Thanks,\n",
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"- IL\n",
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" ---- brought to you by your neighborhood Lerxst ----\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"\n"
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]
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}
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],
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"source": [
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"print(newsgroups[0])"
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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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"## Naiwne przeszukiwanie"
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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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"source": [
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"all_documents = list() \n",
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"for document in newsgroups:\n",
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" if 'car' in document:\n",
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" all_documents.append(document)"
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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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"From: lerxst@wam.umd.edu (where's my thing)\n",
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"Subject: WHAT car is this!?\n",
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"Nntp-Posting-Host: rac3.wam.umd.edu\n",
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"Organization: University of Maryland, College Park\n",
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"Lines: 15\n",
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"\n",
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" I was wondering if anyone out there could enlighten me on this car I saw\n",
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"the other day. It was a 2-door sports car, looked to be from the late 60s/\n",
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"early 70s. It was called a Bricklin. The doors were really small. In addition,\n",
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"the front bumper was separate from the rest of the body. This is \n",
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"all I know. If anyone can tellme a model name, engine specs, years\n",
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"of production, where this car is made, history, or whatever info you\n",
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"have on this funky looking car, please e-mail.\n",
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"\n",
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"Thanks,\n",
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"- IL\n",
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" ---- brought to you by your neighborhood Lerxst ----\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"\n"
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]
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}
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],
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"source": [
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"print(all_documents[0])"
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"From: guykuo@carson.u.washington.edu (Guy Kuo)\n",
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"Subject: SI Clock Poll - Final Call\n",
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"Summary: Final call for SI clock reports\n",
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"Keywords: SI,acceleration,clock,upgrade\n",
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"Article-I.D.: shelley.1qvfo9INNc3s\n",
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"Organization: University of Washington\n",
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"Lines: 11\n",
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"NNTP-Posting-Host: carson.u.washington.edu\n",
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"\n",
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"A fair number of brave souls who upgraded their SI clock oscillator have\n",
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"shared their experiences for this poll. Please send a brief message detailing\n",
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"your experiences with the procedure. Top speed attained, CPU rated speed,\n",
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"add on cards and adapters, heat sinks, hour of usage per day, floppy disk\n",
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"functionality with 800 and 1.4 m floppies are especially requested.\n",
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"\n",
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"I will be summarizing in the next two days, so please add to the network\n",
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"knowledge base if you have done the clock upgrade and haven't answered this\n",
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"poll. Thanks.\n",
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"\n",
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"Guy Kuo <guykuo@u.washington.edu>\n",
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"\n"
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]
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}
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],
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"source": [
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"print(all_documents[1])"
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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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"### jakie są problemy z takim podejściem?\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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"## TFIDF i odległość cosinusowa- gotowe biblioteki"
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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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"source": [
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"vectorizer = TfidfVectorizer()\n",
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"#vectorizer = TfidfVectorizer(use_idf = False, ngram_range=(1,2))"
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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": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"document_vectors = vectorizer.fit_transform(newsgroups)"
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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": 10,
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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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"<11314x130107 sparse matrix of type '<class 'numpy.float64'>'\n",
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"\twith 1787565 stored elements in Compressed Sparse Row format>"
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]
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},
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"execution_count": 10,
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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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"document_vectors"
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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": 11,
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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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"<1x130107 sparse matrix of type '<class 'numpy.float64'>'\n",
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"\twith 89 stored elements in Compressed Sparse Row format>"
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]
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},
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"execution_count": 11,
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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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"document_vectors[0]"
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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": 12,
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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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"matrix([[0., 0., 0., ..., 0., 0., 0.]])"
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]
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},
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"execution_count": 12,
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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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"document_vectors[0].todense()"
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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": 13,
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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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"matrix([[0., 0., 0., ..., 0., 0., 0.],\n",
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" [0., 0., 0., ..., 0., 0., 0.],\n",
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" [0., 0., 0., ..., 0., 0., 0.],\n",
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" [0., 0., 0., ..., 0., 0., 0.]])"
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]
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},
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"execution_count": 13,
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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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"document_vectors[0:4].todense()"
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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": 14,
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"metadata": {},
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"outputs": [],
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"source": [
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"query_str = 'speed'\n",
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"#query_str = 'speed car'\n",
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"#query_str = 'spider man'"
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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": 15,
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"metadata": {},
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"outputs": [],
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"source": [
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"query_vector = vectorizer.transform([query_str])"
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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": 16,
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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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"<11314x130107 sparse matrix of type '<class 'numpy.float64'>'\n",
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"\twith 1787565 stored elements in Compressed Sparse Row format>"
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]
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},
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"execution_count": 16,
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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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"document_vectors"
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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": 17,
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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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"<1x130107 sparse matrix of type '<class 'numpy.float64'>'\n",
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"\twith 1 stored elements in Compressed Sparse Row format>"
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]
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},
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"execution_count": 17,
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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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"query_vector"
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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": 18,
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"metadata": {},
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"outputs": [],
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"source": [
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"similarities = sklearn.metrics.pairwise.cosine_similarity(query_vector,document_vectors)"
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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": 19,
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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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"array([0.26949927, 0.3491801 , 0.44292083, 0.47784165])"
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]
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},
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"execution_count": 19,
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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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"np.sort(similarities)[0][-4:]"
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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": 20,
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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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"array([4517, 5509, 2116, 9921])"
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]
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},
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"execution_count": 20,
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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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"similarities.argsort()[0][-4:]"
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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": 21,
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"metadata": {
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"scrolled": false
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},
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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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"From: ray@netcom.com (Ray Fischer)\n",
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"Subject: Re: x86 ~= 680x0 ?? (How do they compare?)\n",
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"Organization: Netcom. San Jose, California\n",
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"Distribution: usa\n",
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"Lines: 36\n",
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"\n",
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"dhk@ubbpc.uucp (Dave Kitabjian) writes ...\n",
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">I'm sure Intel and Motorola are competing neck-and-neck for \n",
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">crunch-power, but for a given clock speed, how do we rank the\n",
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">following (from 1st to 6th):\n",
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"> 486\t\t68040\n",
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"> 386\t\t68030\n",
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"> 286\t\t68020\n",
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"\n",
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"040 486 030 386 020 286\n",
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"\n",
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">While you're at it, where will the following fit into the list:\n",
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"> 68060\n",
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"> Pentium\n",
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"> PowerPC\n",
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"\n",
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"060 fastest, then Pentium, with the first versions of the PowerPC\n",
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"somewhere in the vicinity.\n",
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"\n",
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">And about clock speed: Does doubling the clock speed double the\n",
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">overall processor speed? And fill in the __'s below:\n",
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"> 68030 @ __ MHz = 68040 @ __ MHz\n",
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"\n",
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"No. Computer speed is only partly dependent of processor/clock speed.\n",
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"Memory system speed play a large role as does video system speed and\n",
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"I/O speed. As processor clock rates go up, the speed of the memory\n",
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"system becomes the greatest factor in the overall system speed. If\n",
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"you have a 50MHz processor, it can be reading another word from memory\n",
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"every 20ns. Sure, you can put all 20ns memory in your computer, but\n",
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"it will cost 10 times as much as the slower 80ns SIMMs.\n",
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"\n",
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"And roughly, the 68040 is twice as fast at a given clock\n",
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"speed as is the 68030.\n",
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"\n",
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"-- \n",
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"Ray Fischer \"Convictions are more dangerous enemies of truth\n",
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"ray@netcom.com than lies.\" -- Friedrich Nietzsche\n",
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"\n",
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"0.4778416465020907\n",
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"----------------------------------------------------------------------------------------------------\n",
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"----------------------------------------------------------------------------------------------------\n",
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"----------------------------------------------------------------------------------------------------\n",
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"From: rvenkate@ux4.cso.uiuc.edu (Ravikuma Venkateswar)\n",
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"Subject: Re: x86 ~= 680x0 ?? (How do they compare?)\n",
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"Distribution: usa\n",
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"Organization: University of Illinois at Urbana\n",
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"Lines: 59\n",
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"\n",
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"ray@netcom.com (Ray Fischer) writes:\n",
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"\n",
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">dhk@ubbpc.uucp (Dave Kitabjian) writes ...\n",
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">>I'm sure Intel and Motorola are competing neck-and-neck for \n",
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">>crunch-power, but for a given clock speed, how do we rank the\n",
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">>following (from 1st to 6th):\n",
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">> 486\t\t68040\n",
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">> 386\t\t68030\n",
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">> 286\t\t68020\n",
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"\n",
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">040 486 030 386 020 286\n",
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"\n",
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"How about some numbers here? Some kind of benchmark?\n",
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"If you want, let me start it - 486DX2-66 - 32 SPECint92, 16 SPECfp92 .\n",
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"\n",
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">>While you're at it, where will the following fit into the list:\n",
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">> 68060\n",
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">> Pentium\n",
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">> PowerPC\n",
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"\n",
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">060 fastest, then Pentium, with the first versions of the PowerPC\n",
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">somewhere in the vicinity.\n",
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"\n",
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"Numbers? Pentium @66MHz - 65 SPECint92, 57 SPECfp92 .\n",
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"\t PowerPC @66MHz - 50 SPECint92, 80 SPECfp92 . (Note this is the 601)\n",
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" (Alpha @150MHz - 74 SPECint92,126 SPECfp92 - just for comparison)\n",
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"\n",
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">>And about clock speed: Does doubling the clock speed double the\n",
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">>overall processor speed? And fill in the __'s below:\n",
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">> 68030 @ __ MHz = 68040 @ __ MHz\n",
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"\n",
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">No. Computer speed is only partly dependent of processor/clock speed.\n",
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">Memory system speed play a large role as does video system speed and\n",
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">I/O speed. As processor clock rates go up, the speed of the memory\n",
|
|
">system becomes the greatest factor in the overall system speed. If\n",
|
|
">you have a 50MHz processor, it can be reading another word from memory\n",
|
|
">every 20ns. Sure, you can put all 20ns memory in your computer, but\n",
|
|
">it will cost 10 times as much as the slower 80ns SIMMs.\n",
|
|
"\n",
|
|
"Not in a clock-doubled system. There isn't a doubling in performance, but\n",
|
|
"it _is_ quite significant. Maybe about a 70% increase in performance.\n",
|
|
"\n",
|
|
"Besides, for 0 wait state performance, you'd need a cache anyway. I mean,\n",
|
|
"who uses a processor that runs at the speed of 80ns SIMMs? Note that this\n",
|
|
"memory speed corresponds to a clock speed of 12.5 MHz.\n",
|
|
"\n",
|
|
">And roughly, the 68040 is twice as fast at a given clock\n",
|
|
">speed as is the 68030.\n",
|
|
"\n",
|
|
"Numbers?\n",
|
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"\n",
|
|
">-- \n",
|
|
">Ray Fischer \"Convictions are more dangerous enemies of truth\n",
|
|
">ray@netcom.com than lies.\" -- Friedrich Nietzsche\n",
|
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"-- \n",
|
|
"Ravikumar Venkateswar\n",
|
|
"rvenkate@uiuc.edu\n",
|
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"\n",
|
|
"A pun is a no' blessed form of whit.\n",
|
|
"\n",
|
|
"0.44292082969477664\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"From: ray@netcom.com (Ray Fischer)\n",
|
|
"Subject: Re: x86 ~= 680x0 ?? (How do they compare?)\n",
|
|
"Organization: Netcom. San Jose, California\n",
|
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"Distribution: usa\n",
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"Lines: 30\n",
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"\n",
|
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"rvenkate@ux4.cso.uiuc.edu (Ravikuma Venkateswar) writes ...\n",
|
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">ray@netcom.com (Ray Fischer) writes:\n",
|
|
">>040 486 030 386 020 286\n",
|
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">\n",
|
|
">How about some numbers here? Some kind of benchmark?\n",
|
|
"\n",
|
|
"Benchmarks are for marketing dweebs and CPU envy. OK, if it will make\n",
|
|
"you happy, the 486 is faster than the 040. BFD. Both architectures\n",
|
|
"are nearing then end of their lifetimes. And especially with the x86\n",
|
|
"architecture: good riddance.\n",
|
|
"\n",
|
|
">Besides, for 0 wait state performance, you'd need a cache anyway. I mean,\n",
|
|
">who uses a processor that runs at the speed of 80ns SIMMs? Note that this\n",
|
|
">memory speed corresponds to a clock speed of 12.5 MHz.\n",
|
|
"\n",
|
|
"The point being the processor speed is only one of many aspects of a\n",
|
|
"computers performance. Clock speed, processor, memory speed, CPU\n",
|
|
"architecture, I/O systems, even the application program all contribute \n",
|
|
"to the overall system performance.\n",
|
|
"\n",
|
|
">>And roughly, the 68040 is twice as fast at a given clock\n",
|
|
">>speed as is the 68030.\n",
|
|
">\n",
|
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">Numbers?\n",
|
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"\n",
|
|
"Look them up yourself.\n",
|
|
"\n",
|
|
"-- \n",
|
|
"Ray Fischer \"Convictions are more dangerous enemies of truth\n",
|
|
"ray@netcom.com than lies.\" -- Friedrich Nietzsche\n",
|
|
"\n",
|
|
"0.3491800997095306\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"From: mb4008@cehp11 (Morgan J Bullard)\n",
|
|
"Subject: Re: speeding up windows\n",
|
|
"Keywords: speed\n",
|
|
"Organization: University of Illinois at Urbana\n",
|
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"Lines: 30\n",
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"\n",
|
|
"djserian@flash.LakeheadU.Ca (Reincarnation of Elvis) writes:\n",
|
|
"\n",
|
|
">I have a 386/33 with 8 megs of memory\n",
|
|
"\n",
|
|
">I have noticed that lately when I use programs like WpfW or Corel Draw\n",
|
|
">my computer \"boggs\" down and becomes really sluggish!\n",
|
|
"\n",
|
|
">What can I do to increase performance? What should I turn on or off\n",
|
|
"\n",
|
|
">Will not loading wallpapers or stuff like that help when it comes to\n",
|
|
">the running speed of windows and the programs that run under it?\n",
|
|
"\n",
|
|
">Thanx in advance\n",
|
|
"\n",
|
|
">Derek\n",
|
|
"\n",
|
|
"1) make sure your hard drive is defragmented. This will speed up more than \n",
|
|
" just windows BTW. Use something like Norton's or PC Tools.\n",
|
|
"2) I _think_ that leaving the wall paper out will use less RAM and therefore\n",
|
|
" will speed up your machine but I could very will be wrong on this.\n",
|
|
"There's a good chance you've already done this but if not it may speed things\n",
|
|
"up. good luck\n",
|
|
"\t\t\t\tMorgan Bullard mb4008@coewl.cen.uiuc.edu\n",
|
|
"\t\t\t\t\t or mjbb@uxa.cso.uiuc.edu\n",
|
|
"\n",
|
|
">--\n",
|
|
">$_ /|$Derek J.P. Serianni $ E-Mail : djserian@flash.lakeheadu.ca $ \n",
|
|
">$\\'o.O' $Sociologist $ It's 106 miles to Chicago,we've got a full tank$\n",
|
|
">$=(___)=$Lakehead University $ of gas, half a pack of cigarettes,it's dark,and$\n",
|
|
">$ U $Thunder Bay, Ontario$ we're wearing sunglasses. -Elwood Blues $ \n",
|
|
"\n",
|
|
"0.26949927393886913\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"----------------------------------------------------------------------------------------------------\n",
|
|
"----------------------------------------------------------------------------------------------------\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"for i in range (1,5):\n",
|
|
" print(newsgroups[similarities.argsort()[0][-i]])\n",
|
|
" print(np.sort(similarities)[0,-i])\n",
|
|
" print('-'*100)\n",
|
|
" print('-'*100)\n",
|
|
" print('-'*100)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Zadanie domowe\n",
|
|
"\n",
|
|
"\n",
|
|
"- Wybrać zbiór tekstowy, który ma conajmniej 5000 dokumentów.\n",
|
|
"- Na jego podstawie stworzyć wyszukiwarkę bazującą na OKAPI BM25, tzn. system który dla podanej frazy podaje kilka (5-10) posortowanych najbardziej pasujących dokumentów. Można korzystać z gotowych bibliotek do wektoryzacji dokumentów, należy jednak samemu zaimplementować OKAPI BM25.\n",
|
|
"- Znaleźć frazę (query), dla której wynik nie jest satysfakcjonujący.\n",
|
|
"- Poprawić wyszukiwarkę (np. poprzez zmianę preprocessingu tekstu, wektoryzer, zmianę parametrów algotytmu rankującego lub sam algorytm) tak, żeby zwracała satysfakcjonujące wyniki dla poprzedniej frazy\n",
|
|
"- prezentować pracę na następnych zajęciach (15.03) odpowiadając na pytania:\n",
|
|
" - jak wygląda zbiór i system wyszukiwania przed zmianami\n",
|
|
" - dla jakiej frazy wyniki są niesatysfakcjonujące (pokazać wyniki)\n",
|
|
" - jakie zmiany zostały naniesione\n",
|
|
" - jak wyglądają wyniki wyszukiwania po zmianach\n",
|
|
" - jak zmiany wpłynęły na wyniki (1-2 zdania)\n",
|
|
" \n",
|
|
"Prezentacja powinna być maksymalnie prosta i trwać maksymalnie 2-3 minuty.\n",
|
|
"punktów do zdobycia: 40\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.8.5"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
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|