"Tokenize" Example Sentences
1. I need to tokenize this sentence into individual words.
2. The first step in natural language processing is to tokenize the text.
3. The program uses regular expressions to tokenize the input.
4. The tokenizer function is crucial for machine learning algorithms.
5. Can you tokenize this data and store it in a database?
6. The tokenizer breaks down the text into chunks for analysis.
7. The NLP model requires tokenized input for accurate results.
8. Tokenizing the text will make it easier to analyze and manipulate.
9. The algorithm needs to tokenize the input before performing calculations.
10. I created a custom tokenizer to handle specific data types.
11. The tokenizer identifies punctuation marks and removes them from the text.
12. Can you tokenize the text and remove any non-alphanumeric characters?
13. The tokenizer is designed to handle different languages and writing systems.
14. The output of the tokenizer will be used as input for the classification model.
15. The tokenizer preprocesses the text by breaking it down into meaningful chunks.
16. The tokenizer can be configured to handle different types of text data.
17. Tokenizing the text is an important step before performing sentiment analysis.
18. The tokenizer converts the text into a format that can be used by machine learning algorithms.
19. The tokenization process eliminates duplicate words and simplifies the data.
20. The tokenizer is part of the preprocessing pipeline for text data.
21. Tokenizing the text helps to identify patterns and relationships in the data.
22. The tokenizer is an essential component of any NLP project.
23. The tokenizer converts unstructured text into structured data for further analysis.
24. Tokenizing the text can improve the accuracy of text-based prediction models.
25. The tokenizer can handle text data in multiple languages and formats.
26. The tokenization process assigns unique identifiers to each token for easy retrieval.
27. Tokenizing the text helps to reduce the dimensionality of the data.
28. The tokenizer is used to preprocess text data for search engines.
29. The tokenization process can be customized to fit specific project requirements.
30. The tokenizer can handle large volumes of text data with minimal processing time.
Common Phases
-
Tokenize the input string;
- The first step is to
tokenize the sentence;
- You need to
tokenize the data for further analysis;
- I can use NLTK library to
tokenize the text;
- Once you
tokenize the text, you can perform natural language processing;
- Let's
tokenize the document to extract important keywords;
- Tokenizing the text will help us understand the structure of the sentence;
- In order to
tokenize the data, we need to specify the delimiter;
- Tokenization is the process of breaking the text into smaller chunks;
- We can use regular expressions to
tokenize the text;
- The
tokenizer function takes a text and returns a list of tokens;
- We need to
tokenize the text before we can analyze it;
- There are different types of
tokenizers available such as word
tokenizer and sentence
tokenizer;
- Tokenization is a key step in many natural language processing tasks;
- The tokenization process can help us understand the semantic meaning of the text;
- Before we can
tokenize the text, we need to preprocess it to remove stop words and punctuation;
- The tokenization algorithm can affect the accuracy of the natural language processing model;
- Tokenizing the text can be a computationally intensive process.