nlp/0_1_NLP_Slides.ipynb

@@ -89,7 +89,7 @@
     }
    },
    "source": [
-    "In this session, we are going to learn to process text so that we can apply machine learning techniques."
+    "In this session we are going to learn to process text so that can apply machine learning techniques."
    ]
   },
   {
@@ -101,7 +101,7 @@
    },
    "source": [
     "# NLP Basics\n",
-    "In this notebook, we are going to use two popular NLP libraries:\n",
+    "In this notebook we are going to use two popular NLP libraries:\n",
     "* NLTK (Natural Language Toolkit, https://www.nltk.org/) \n",
     "* Spacy (https://spacy.io/)"
    ]
@@ -116,7 +116,7 @@
    "source": [
     "Main characteristics:\n",
     "* both are open source and very popular\n",
-    "* NLTK was released in 2001, while Spacy was in 2015\n",
+    "* NLTK was released in 2001 while Spacy was in 2015\n",
     "* Spacy provides very efficient implementations"
    ]
   },
@@ -130,7 +130,7 @@
    "source": [
     "# Spacy installation\n",
     "\n",
-    "You need to install spacy if not installed:\n",
+    "You need to install previously spacy if not installed:\n",
     "* `pip install spacy`\n",
     "* or `conda install -c conda-forge spacy`\n",
     "\n",
@@ -148,7 +148,7 @@
    "source": [
     "# Spacy pipelines\n",
     "\n",
-    "The function **nlp** takes a raw text and performs several operations (tokenization, tagger, NER, ...)\n",
+    "The function **nlp** takes a raw text and perform several operations (tokenization, tagger, NER, ...)\n",
     "![](spacy/spacy-pipeline.svg \"Spacy pipelines\")"
    ]
   },
@@ -160,7 +160,7 @@
     }
    },
    "source": [
-    "From text to doc through the pipeline"
+    "From text to doc trough the pipeline"
    ]
   },
   {
@@ -205,7 +205,7 @@
     "\n",
     "* **Tokenizer exception:** Special-case rule to split a string into several tokens or prevent a token from being split when punctuation rules are applied.\n",
     "* **Prefix:** Character(s) at the beginning, e.g. $, (, “, ¿.\n",
-    "* **Suffix:** Character(s) at the end, e.g. km, ”, !.\n",
+    "* **Suffix:** Character(s) at the end, e.g. km, ), ”, !.\n",
     "* **Infix:** Character(s) in between, e.g. -, --, /, …."
    ]
   },

nlp/0_2_NLP_Assignment.ipynb

@@ -82,7 +82,7 @@
     }
    },
    "source": [
-    "### 1. List the first 10 tokens of the doc."
+    "### 1. List the first 10 tokens of the doc"
    ]
   },
   {
@@ -149,7 +149,7 @@
     }
    },
    "source": [
-    "###  7. Visualize the dependency grammar analysis of the second sentence."
+    "###  7. Visualize the dependency grammar analysis of the second sentence"
    ]
   },
   {
@@ -178,7 +178,7 @@
     }
    },
    "source": [
-    "### 9. List the frequencies of POS in the document in a table."
+    "### 9. List frequencies of POS in the document in a table "
    ]
   },
   {
@@ -191,7 +191,7 @@
    "source": [
     "### 10. Preprocessing\n",
     "\n",
-    "Remove from the doc stopwords, digits, and punctuation.\n",
+    "Remove from the doc stopwords, digits and punctuation.\n",
     "\n",
     "Hint: check the token api https://spacy.io/api/token\n",
     "\n",
@@ -207,7 +207,7 @@
    },
    "source": [
     "### 11. Entities of the document\n",
-    "Print the entities of the document, the type of the entity, and the explanation of the entity in a table with three columns.\n",
+    "Print the entities of the document, the type of the entity and what the explanation of the entity in a table with three columns.\n",
     "\n",
     "Example:\n",
     "\n",
@@ -223,7 +223,7 @@
    },
    "source": [
     "### 12. Visualize the entities\n",
-    "Show the entities highlighted in the text."
+    "Show the entities in a graph."
    ]
   },
   {
@@ -236,7 +236,7 @@
    "source": [
     "# Movie review\n",
     "\n",
-    "Classify the movie reviews from the following dataset  https://data.world/rajeevsharma993/movie-reviews"
+    "Classify the rmoview reviews from the following dataset  https://data.world/rajeevsharma993/movie-reviews"
    ]
   },
   {