pos exercise link

sheikhasim · May 11, 2022 · 80eb297 · 80eb297
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diff --git a/7_pos/part_of_speech_in_spacy.ipynb b/7_pos/part_of_speech_in_spacy.ipynb
@@ -221,8 +221,10 @@
   },
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+   "execution_count": 50,
+   "metadata": {
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      "data": {
@@ -236,182 +238,16 @@
        " results,\n",
        " for,\n",
        " the,\n",
-       " quarter,\n",
-       " ended,\n",
-       " December,\n",
-       " 31,\n",
-       " 2021,\n",
-       " as,\n",
-       " compared,\n",
-       " to,\n",
-       " the,\n",
-       " corresponding,\n",
-       " period,\n",
-       " of,\n",
-       " last,\n",
-       " fiscal,\n",
-       " year,\n",
-       " Revenue,\n",
-       " was,\n",
-       " $,\n",
-       " 51.7,\n",
-       " billion,\n",
-       " and,\n",
-       " increased,\n",
-       " 20,\n",
-       " %,\n",
-       " Operating,\n",
-       " income,\n",
-       " was,\n",
-       " $,\n",
-       " 22.2,\n",
-       " billion,\n",
-       " and,\n",
-       " increased,\n",
-       " 24,\n",
-       " %,\n",
-       " Net,\n",
-       " income,\n",
-       " was,\n",
-       " $,\n",
-       " 18.8,\n",
-       " billion,\n",
-       " and,\n",
-       " increased,\n",
-       " 21,\n",
-       " %,\n",
-       " Diluted,\n",
-       " earnings,\n",
-       " per,\n",
-       " share,\n",
-       " was,\n",
-       " $,\n",
-       " 2.48,\n",
-       " and,\n",
-       " increased,\n",
-       " 22,\n",
-       " %,\n",
-       " Digital,\n",
-       " technology,\n",
-       " is,\n",
-       " the,\n",
-       " most,\n",
-       " malleable,\n",
-       " resource,\n",
-       " at,\n",
-       " the,\n",
-       " world,\n",
-       " ’s,\n",
-       " disposal,\n",
-       " to,\n",
-       " overcome,\n",
-       " constraints,\n",
-       " and,\n",
-       " reimagine,\n",
-       " everyday,\n",
-       " work,\n",
-       " and,\n",
-       " life,\n",
-       " said,\n",
-       " Satya,\n",
-       " Nadella,\n",
-       " chairman,\n",
-       " and,\n",
-       " chief,\n",
-       " executive,\n",
-       " officer,\n",
-       " of,\n",
-       " Microsoft,\n",
-       " As,\n",
-       " tech,\n",
-       " as,\n",
-       " a,\n",
-       " percentage,\n",
-       " of,\n",
-       " global,\n",
-       " GDP,\n",
-       " continues,\n",
-       " to,\n",
-       " increase,\n",
-       " we,\n",
-       " are,\n",
-       " innovating,\n",
-       " and,\n",
-       " investing,\n",
-       " across,\n",
-       " diverse,\n",
-       " and,\n",
-       " growing,\n",
-       " markets,\n",
-       " with,\n",
-       " a,\n",
-       " common,\n",
-       " underlying,\n",
-       " technology,\n",
-       " stack,\n",
-       " and,\n",
-       " an,\n",
-       " operating,\n",
-       " model,\n",
-       " that,\n",
-       " reinforces,\n",
-       " a,\n",
-       " common,\n",
-       " strategy,\n",
-       " culture,\n",
-       " and,\n",
-       " sense,\n",
-       " of,\n",
-       " purpose,\n",
-       " Solid,\n",
-       " commercial,\n",
-       " execution,\n",
-       " represented,\n",
-       " by,\n",
-       " strong,\n",
-       " bookings,\n",
-       " growth,\n",
-       " driven,\n",
-       " by,\n",
-       " long,\n",
-       " term,\n",
-       " Azure,\n",
-       " commitments,\n",
-       " increased,\n",
-       " Microsoft,\n",
-       " Cloud,\n",
-       " revenue,\n",
-       " to,\n",
-       " $,\n",
-       " 22.1,\n",
-       " billion,\n",
-       " up,\n",
-       " 32,\n",
-       " %,\n",
-       " year,\n",
-       " over,\n",
-       " year,\n",
-       " said,\n",
-       " Amy,\n",
-       " Hood,\n",
-       " executive,\n",
-       " vice,\n",
-       " president,\n",
-       " and,\n",
-       " chief,\n",
-       " financial,\n",
-       " officer,\n",
-       " of,\n",
-       " Microsoft]"
+       " quarter]"
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+     "execution_count": 50,
      "metadata": {},
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    "source": [
-    "filtered_tokens"
+    "filtered_tokens[:10]"
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diff --git a/7_pos/pos_exercise.md b/7_pos/pos_exercise.md
@@ -1,9 +1,9 @@
 Exercise for Spacy POS tutorial,
 
-1) You are parsing a news story from cnbc.com. News story is stores in [news_story.txt]() which is available in this same folder on github. You need to,
+1) You are parsing a news story from cnbc.com. News story is stores in [news_story.txt](https://github.com/codebasics/nlp-tutorials/blob/main/7_pos/news_story.txt) which is available in this same folder on github. You need to,
    1) Extract all NOUN tokens from this story. You will have to read the file in python first to collect all the text and then extract NOUNs in a python list
    2) Extract all numbers (NUM POS type) in a python list
    3) Print a count of all POS tags in this story
 
-[Solution]()
+[Solution](https://github.com/codebasics/nlp-tutorials/blob/main/7_pos/Exercise/pos_exercise_solution.ipynb)