[TA] modified letter cases in README.md (Azure#28711)

sdk/textanalytics/azure-ai-textanalytics/README.md

@@ -235,7 +235,7 @@ The following section provides several code snippets covering some of the most c
 - [Abstractive Summarization][abstract_summary_sample]
 - [Dynamic Classification][dynamic_classification_sample]
 
-### Analyze sentiment
+### Analyze Sentiment
 
 [analyze_sentiment][analyze_sentiment] looks at its input text and determines whether its sentiment is positive, negative, neutral or mixed. It's response includes per-sentence sentiment analysis and confidence scores.
 
@@ -270,7 +270,7 @@ The returned response is a heterogeneous list of result and error objects: list[
 
 Please refer to the service documentation for a conceptual discussion of [sentiment analysis][sentiment_analysis]. To see how to conduct more granular analysis into the opinions related to individual aspects (such as attributes of a product or service) in a text, see [here][opinion_mining_sample].
 
-### Recognize entities
+### Recognize Entities
 
 [recognize_entities][recognize_entities] recognizes and categories entities in its input text as people, places, organizations, date/time, quantities, percentages, currencies, and more.
 
@@ -307,7 +307,7 @@ The returned response is a heterogeneous list of result and error objects: list[
 Please refer to the service documentation for a conceptual discussion of [named entity recognition][named_entity_recognition]
 and [supported types][named_entity_categories].
 
-### Recognize linked entities
+### Recognize Linked Entities
 
 [recognize_linked_entities][recognize_linked_entities] recognizes and disambiguates the identity of each entity found in its input text (for example,
 determining whether an occurrence of the word Mars refers to the planet, or to the
@@ -347,7 +347,7 @@ The returned response is a heterogeneous list of result and error objects: list[
 Please refer to the service documentation for a conceptual discussion of [entity linking][linked_entity_recognition]
 and [supported types][linked_entities_categories].
 
-### Recognize PII entities
+### Recognize PII Entities
 
 [recognize_pii_entities][recognize_pii_entities] recognizes and categorizes Personally Identifiable Information (PII) entities in its input text, such as
 Social Security Numbers, bank account information, credit card numbers, and more.
@@ -385,7 +385,7 @@ Please refer to the service documentation for [supported PII entity types][pii_e
 
 Note: The Recognize PII Entities service is available in API version v3.1 and newer.
 
-### Extract key phrases
+### Extract Key Phrases
 
 [extract_key_phrases][extract_key_phrases] determines the main talking points in its input text. For example, for the input text "The food was delicious and there were wonderful staff", the API returns: "food" and "wonderful staff".
 
@@ -417,7 +417,7 @@ The returned response is a heterogeneous list of result and error objects: list[
 
 Please refer to the service documentation for a conceptual discussion of [key phrase extraction][key_phrase_extraction].
 
-### Detect language
+### Detect Language
 
 [detect_language][detect_language] determines the language of its input text, including the confidence score of the predicted language.