Nlp python. Stop using the Python virtual environment: deactivate.
spaCy is the perfect toolkit Aug 14, 2020 · 1. Afterward, we will discuss the basics of other Natural Language Processing libraries and other essential methods for NLP, along with their respective coding sample implementations in Python. Indian languages share a lot of similarity in terms of script, phonology, language syntax, etc. 7. It’s in many existing production systems due to its speed. Remove ads. For detailed information please visit our official website. It has many applications in healthcare, customer service, banking, etc. As a facade of the award-winning Spark NLP library, it comes with 1000+ of pretrained models in 100+ , all production-grade, scalable, and trainable, with Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. Refresh. May 19, 2021 · In this post I want to demonstrate how you can use the awesome Python packages, spaCy and Pandas, to structure natural language and extract interesting insights quickly. Feb 19, 2022 · POS Tagging [NLP, Python] POS tagging is important to get an idea that which parts of speech does tokens belongs to i. More modern techniques, such as deep learning, have produced results in the fields of language modeling, parsing, and spaCy is a fast and powerful library for natural language processing in Python. pip install jupyterlab pip install python-Levenshtein pip install bert-serving-server bert-serving Apr 29, 2023 · Tokenization is a crucial step in many Natural Language Processing (NLP) tasks. Natural language processing (NLP) is a widely discussed and studied subject these days. SnowNLP (Python) Python library for processing Chinese text. Sentiment Analysis. The natural language processing (NLP) pipeline refers to the sequence of processes involved in analyzing and understanding human languag Knowledge-sharing platform Zhihu provides a space for users to write and express themselves freely. Apr 28, 2020 · Short for Natural Language ToolKit, NLTK is the leading and one of the best Natural Language Processing libraries for Python. If you’re working with a lot of text, you’ll eventually want to know more about it. NLP can help you with lots of tasks and the fields of application just seem to increase on a daily basis. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. These include applications like sentiment analysis, semantic parsing, or spam filtering. The output of this method will be: Aug 4, 2009 · Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis; Access popular linguistic databases, including WordNet and treebanks Feb 15, 2023 · We’ll also see an implementation of the same in Python. Step #2: Forming the Lists of Keywords. Natural Language Processing (NLP) is a critical component of modern AI, enabling machines to understand and respond to human language. Jan 12, 2017 · The python wrapper StanfordCoreNLP (by Stanford NLP Group, only commercial license) and NLTK dependency grammars can be used to generate dependency trees. It offers high-speed performance, making it particularly effective in product development contexts. KerasNLP is a high-level NLP modeling library that includes all the latest transformer-based models as well as lower-level tokenization utilities. This blog covers data preparation, tokenization, part-of-speech tagging, and more. Natural language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data. If you are new to Python, this is a good place to get started. 在本NLP教程包含了一些范例，涵盖了大多数常见NLP任务，是入门NLP和PyTorch的学习资料，也可以作为 Add this topic to your repo. NLP is a topic that intersects with AI, computer science, and linguistics. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize Important points and code from the famous book: Natural Language Processing using python by Steven Bird, Ewan Klein and Edward Loper python nlp machine-learning nlp-machine-learning nlp-projects Updated May 5, 2018 UPDATE #3: More wild stabs at finding a Python-based solver yielded PyGMO, which is a set of Python bindings to PaGMO, a C++ based global multiobjective optimization solver. This technology is one of the most broadly applied areas of machine learning and is critical in effectively analyzing massive quantities of unstructured, text-heavy data. By the end of the program, you will have the theoretical Jun 9, 2020 · Stanford’s CoreNLP is a Java library with Python wrappers. NLTK is widely used by researchers, developers, and data scientists worldwide to Jun 22, 2021 · Let’s define Natural Language Processing (NLP) formally, Natural language Processing (NLP) is a subfield of artificial intelligence, that involves the interactions between computers and humans. The tokens can be either characters, subwords, words, or a mix of all three. Jul 25, 2023 · Originally published on Towards AI. It is designed to extract semantic topics from documents. Jul 5, 2017 · Natural language processing is a powerful skill that helps you derive immense value from that data. The course is as much interactive as possible to better internalize the concepts: Aug 3, 2020 · Natural language processing (NLP) is a specialized field for analysis and generation of human languages. your favorite neural NER system) to the CoreNLP pipeline via a lightweight service. CoreNLP. Jan 15, 2019 · Use Cases of NLP. Nov 7, 2022 · Gensim: It is an open source library in python written by Radim Rehurek which is used in unsupervised topic modelling and natural language processing. Welcome to KGP Talkie's Natural Language Processing (NLP) course. The method iterates all the sentences and adds the extracted word into an array. I have used and tested the scripts in Python 3. (Remember the joke where the wife asks the husband to "get a carton of milk and if they have eggs, get NLU: The Power of Spark NLP, the Simplicity of Python John Snow Labs' NLU is a Python library for applying state-of-the-art text mining, directly on any dataframe, with a single line of code. In other words, Natural Language Processing can be used to create a new intelligent system that can understand how humans understand and interpret language in different situations. HanLP (Java) FastNLP (Python) 一款轻量级的 NLP 处理套件。. In this post, we will learn how to identity which topic is discussed in a document, called topic modelling. Let’s make sure you have the right tools before we get The Cloud NLP API is used to improve the capabilities of the application using natural language processing technology. It helps convert text into numbers, which the model can then easily work with. The main goal is to enable a computer to compare, classify, and organize textual data based Jul 22, 2020 · Therefore, Natural Language Processing (NLP) has a non-deterministic approach. We'll be looking at a dataset consisting of sublessons to Hacker News from 2006 to 2015. by widodo · Published March 9, 2021 · Updated March 9, 2021. It allows you to carry various natural language processing functions like sentiment analysis and language detection. BertSpanLabeler class implements a simple single-span start-end predictor (that is, a model that predicts two values: a start token index and an end token index), suitable for SQuAD-style tasks. Oct 17, 2023 · The nlp. Also, install Jupyter Lab and a few Python modules. Twitter is great for mining trends and sentiment. Python setup 🔧. The most important concepts, explained in simple terms. Many of the concepts (such as the computation graph abstraction and autograd) are not unique to Pytorch and are relevant to any deep learning toolkit out there. To associate your repository with the vietnamese-nlp topic, visit your repo's landing page and select "manage topics. Jun 9, 2021 · 7. Natural Language Toolkit¶. Human languages, rightly called natural language, are highly context-sensitive and often ambiguous in order to produce a distinct meaning. Following your definition, add the highlighted code to create tokens for the two statements you’ll be comparing. It’s not as widely adopted, but if you’re building a new application, you should give it a try. Feb 2, 2022 · 4. For example: pip install spark-nlp pip install pyspark. load("pt_core_news_sm") nlp-tutorial. This free and open-source library for natural language processing (NLP) in Python has a lot of built-in capabilities and is becoming increasingly popular for processing and analyzing data in NLP. In this track, you’ll gain the core Natural Language Processing (NLP) skills you need to convert that data into valuable insights—from learning how to automatically transcribe TED talks Jan 24, 2023 · Part-of-speech (POS) tagging is fundamental in natural language processing (NLP) and can be done in Python. After the get_weather() function in your file, create a chatbot() function representing the chatbot that will accept a user’s statement and return a response. Stop using the Python virtual environment: deactivate. NLTK’s goal is to make learning and working with computational linguistics easier by Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit Steven Bird, Ewan Klein, and Edward Loper. download('punkt') text = "Tokenization is the process of breaking down a large text into smaller chunks called tokens. It is designed to give you a complete understanding of Text Processing and Mining with the use of State-of-the-Art NLP algorithms in Python. Python NLP Libraries: Dive into courses that delve into Python libraries like NLTK, spaCy, and Transformers. Jan 9, 2023 · Fig 2. This article aims to begin understanding how value can be gained by using a few Python packages. Introduction to NLP and PyTorch. At the time of writing this tutorial, we’re using version 3. Jul 24, 2023 · We dive into the natural language toolkit (NLTK) library to present how it can be useful for natural language processing related tasks. The book focuses on using the NLTK Python library, which is very popular for common NLP tasks. The data was taken from here. . Setelah sebelumnya kita mencoba untuk menampilkan kata-kata dalam sebuah tulisan sebuah berita dalam Oct 13, 2023 · A lot of tasks in NLP start by tokenizing the text². Let’s get started!” May 19, 2023 · To install Spark NLP in Python, simply use your favorite package manager (conda, pip, etc. models. Analyzing Tweets with Sentiment Analysis and Python In this last section, you'll take what you have learned so far in this post and put it into practice with a fun little project: analyzing tweets about NFTs with sentiment analysis! First, you'll use Tweepy, an easy-to-use Python library for getting tweets mentioning #NFTs using the Twitter Sentiment analysis is the practice of using algorithms to classify various samples of related text into overall positive and negative categories. net May 14, 2021 · In this tutorial, we’ll use Python’s nltk library to perform all NLP operations on the text. PyTorch, a popular open-source machine learning library, provides robust tools for NLP tasks due to its flexibility May 16, 2023 · The open-source Python library Spark NLP implemented two models for ASR: Facebook’s Wav2Vec version 2. It involves labelling words in a sentence with their corresponding POS tags. It is a subset of artificial intelligence that enables machines to comprehend and analyze human languages. . I demonstrated how to parse text and define stopwords in Python and introduced the concept of a corpus, a dataset of text that aids in text processing with out-of-the-box data. Jan 13, 2019 · Project description. ). and this library is an attempt to provide a general solution to very commonly required toolsets for May 30, 2023 · Learn the basics of NLP, its applications, and popular Python libraries for text analysis. SpaCy is “spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python”, developed by explosion_ai. Hence it makes it different from other machine learning software packages which target memory Aug 7, 2020 · In my previous article, I introduced natural language processing (NLP) and the Natural Language Toolkit (), the NLP toolkit created at the University of Pennsylvania. This video will provide you with a comprehensive and detailed knowledge of Natural Language Processing. 4 of nltk . Step #3: Streamlining the Job Descriptions using NLP Techniques. Documents, annotations and corpora spaCy is a modern Python library for industrial-strength Natural Language Processing. This article is part of a blog series on Natural Language Processing Feb 19, 2020 · Step #2: Forming the Lists of Keywords. SpaCy is a new NLP library that’s designed to be fast, streamlined, and production-ready. load ("en_core_web_md") . Pricing: Cloud NLP API is available for free. Wordcloud. Natural language processing (NLP) is an interdisciplinary subfield of computer science and artificial intelligence. We have a large collection of NLP libraries available in Python. Step #4: Final Processing of the Keywords and the Job Descriptions. It provides a wide range of software, models, and datasets for Thai language. And we will apply LDA to convert set of research papers to a set of topics. Jun 9, 2015 · Python has some powerful tools that enable you to do natural language processing (NLP). 自然语言处理（NLP）教程，包括：文本词向量，词法分析，预训练语言模型，文本分类，文本语义相似度计算，文本生成，实体识别，翻译，对话。. With NLTK, you can employ these algorithms through powerful built-in machine learning operations to obtain insights from linguistic data. POS tags indicate the grammatical category of a word, such as noun, verb, adjective, adverb, etc. It has over 100 corpora and related lexical resources, such as WordNet, Web Text Corpus, NPS Chat, SemCor, FrameNet and many more. 2. This package contains a python interface for Stanford CoreNLP that contains a reference implementation to interface with the Stanford CoreNLP server . This includes information recorded in books, online articles, and audio files. Before searching in the job descriptions, we need lists of keywords that represent the tools/skills/degrees. This version of the NLTK book is updated for Python 3 and NLTK 3. To run these examples, you need Python 3. , a comment, review, or a document) and determines whether data is positive, negative, or neutral. NLTK is a leading platform for building Python programs to work with human language data. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. In this free and interactive online course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches. abstract = "We present PyThaiNLP, a free and open-source natural language processing (NLP) library for Thai language implemented in Python. It is easy to use. First, we need a dataset to work with and Kaggle is where we have gone to. Looking at the data. 📚 Check out our tutorial on the Bernoulli distribution with code examples in Python Jun 7, 2020 · 0. Getting Ready. We'll understand fundamental NLP concepts such as stemming, lemmatization, stop Dec 15, 2022 · Create an account or log in. Similarity Measures in natural language processing (NLP) is to quantify the similarity or dissimilarity between two pieces of text or collections of text, such as documents, sentences, or words. extend (w) words = sorted (list (set (words))) return words. Dec 8, 2020 · Dec 8, 2020. As digital interactions proliferate, NLP's importance grows. Python for Natural Language Processing: A Beginner’s GuideIntroduction Natural Language Processing (NLP) is the study of making natural human language readable to computer programs. Mar 27, 2023 · Python is a popular programming language used for Natural Language Processing (NLP) due to its simplicity, flexibility, and a large number of libraries and tools available. In this video we go through the major concepts in natural language processing using Python libraries! We use examples to help drill down the concepts. With the Tweepy Python library, you can easily pull a constant stream of tweets based on the desired topics. For this analysis, we use a simple approach to forming the lists. The article explores the basics of keyword extraction, its significance in NLP, and various implementation methods using Python libraries like NLTK, TextRank, RAKE, YAKE, and Feb 21, 2024 · NLTK. " GitHub is where people build software. Mar 9, 2021 · NLP Sederhana Dengan Python. Arnaud Drizard used the Hacker News API to Apr 1, 2021 · Step 4: Extracting vectors from text (Vectorization) It’s difficult to work with text data while building Machine learning models since these models need well-defined numerical data. Mar 30, 2018 · Topic Modelling in Python with NLTK and Gensim. It supports various tasks, such as tokenization, part-of-speech tagging, dependency parsing, named entity recognition, sentiment analysis, and more. It's the recommended solution for most NLP use cases. In this post we will be using datasets hosted by Kaggle and considering the content-based approach, we will be building job recommendation systems. Text tokenization is a process where we split the original text into smaller parts — tokens. However, you ask me to pick the most important ones, here they are. Spacy’s datamodel for documents is The Natural Language Toolkit (NLTK) is a popular open-source library for natural language processing (NLP) in Python. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and May 26, 2024 · Natural Language Processing is referred to as NLP. It is a fast-expanding field with important applications in banking Mar 7, 2021 · $ python -m spacy download pt_core_news_sm A partir disso, podemos simplesmente carregar esse modelo pré-treinado dessa forma: nlp = spacy. Jul 7, 2019 · Introduction. 0 and HuBERT that achieve state-of-the-art accuracy on most of the public datasets. Pada tulisan kali ini kita akan coba untuk melanjutkan bahasan tulisan sebelumnya mengenai wordcloud dengan python Membuat Wordcloud Dengan Python. The process Nov 2, 2021 · Python | NLP analysis of Restaurant reviews. Written by Steven Bird, Ewan Klein and Edward Loper. Delete your virtual environment folder: cd ~ ; rm -rf . These are usually the Natural Language Understanding tasks. Dec 19, 2021 · The NLP techniques or applications that should use stopword removal in the pipeline are ones that revolve around meaning. Jul 11, 2024 · HanLP is a Python package for natural language processing of Han languages, such as Chinese, Japanese, and Korean. HanLP is easy to install and use, and can be integrated with other PyPI packages. Preparation: Scraping the Data. It provides an easy-to-use interface for a wide range of tasks, including tokenization, stemming, lemmatization, parsing, and sentiment analysis. The tasks that don’t require stop words are ones which don’t Dec 18, 2018 · Step 2: Apply tokenization to all sentences. It contains support for running various accurate natural language processing tools on 60+ languages and for accessing the Java Stanford CoreNLP software from Python. Aug 21, 2019 · Overview. It is primarily concerned with providing computers the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics. It can handle large text collections. Introducing SpaCy. Sep 27, 2018 · Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret, and manipulate human language. Jun 8, 2023 · Keyword extraction is a vital task in Natural Language Processing (NLP) for identifying the most relevant words or phrases from text, and enhancing insights into its content. spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. Natural Language Processing with Python. NLP Introduction: Enroll in introductory NLP courses, ensuring they use Python for demonstrations and hands-on exercises. Jul 28, 2023 · TensorFlow provides two libraries for text and natural language processing: KerasNLP ( GitHub) and TensorFlow Text ( GitHub ). Although it was created for multiobjective optimization, it can also be used to single objective nonlinear programming, and has Python interfaces to IPOPT and SNOPT, among Afterwards we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state of the art Spacy library for ultra fast tokenization, parsing, entity recognition, and lemmatization of text. Natural Language Processing. We first provide a brief historical context of tools for Thai language prior to the development of PyThaiNLP. In this course, Getting Started with Natural Language Processing with Python, you'll first learn about using the Natural Language Toolkit to pre-process raw text. It’s what helps you translate text, filter spam, and detect fake news. It supports 75+ languages, pretrained transformers, custom components, and easy deployment. Next, you'll learn how to scrape websites for texting using BeautifulSoup, as well This tutorial will walk you through the key ideas of deep learning programming using Pytorch. e whether it is noun, verb, adverb… Feb 27, 2022 Jul 17, 2021 · Time to call on the Natural Language Processing (NLP) algorithms. I am writing this tutorial to focus specifically on NLP for people who have never written Python Basics: If you're a beginner, start with foundational Python programming courses. It provides very flexible representations of documents, stand-off annotations with arbitrary types and features, grouped into arbitrary annotations sets, spans, corpora, annotators, pipelines and more. in Python. Stanza is a Python natural language analysis package. FudanNLP by 复旦 (Java) BaiduLac by 百度 Baidu's open-source lexical analysis tool for Chinese, including word segmentation, part-of-speech tagging & named entity recognition. I assume the reader (👀 yes, you!) has access to and is familiar with Python including installing packages, defining functions and other basic tasks. Here’s some sample Python code to illustrate tokenization using the popular NLTK library: import nltk nltk. Intending to extract value from text, they help to separate the wheat from the chaff. def tokenize (sentences): words = [] for sentence in sentences: w = word_extraction (sentence) words. Feb 28, 2020 · Table Of Contents. Setting up a development environment with the right tools and packages is essential for efficient and effective NLP work. The goal of POS tagging is to determine a sentence’s The Stanford NLP Group's official Python NLP library. NLP, one of the oldest areas of machine learning research, is used in major fields such as Natural Language Processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence that uses algorithms to interpret and manipulate human language. 7 Theoretical Overview LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. CoreNLP is a Java-based library, serving as a Natural Language Processing Python example, developed by Stanford University, notable for its precision in Natural Language parsing and comprehensive linguistic annotations. In simple terms, NLP represents the automatic handling of natural human language like speech or text, and although the concept itself is fascinating, the real value behind this technology comes from the use cases. In this step-by-step tutorial, you'll learn how to use spaCy. networks. Introduction to Spacy spaCy is a very popular Python package for advanced NLP — I have a beginner friendly introduction to NLP with SpaCy here . You learned how to use the Natural Language API using Python! To clean up your development environment, from Cloud Shell: If you're still in your IPython session, go back to the shell: exit. This course covers the basics of NLP to advance topics While gaining valuable practice with Python functions and expressions, you will also master the ability to process text using NLP-specific packages, including Natural Language Tool Kit (NLTK), Gensim, spaCy, regex, and SentenceTransformers, that can be used to extend Python’s power. In short, this technology allows a machine to understand and process human language. Oct 14, 2020 · In this article, you will learn from the basic (and advanced) concepts of NLP to implement state of the art problems like Text Summarization, Classification, etc. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. 1. Initially, the spaCy English model is loaded, and the sample text, “There is a pen on the table,” is processed using spaCy. Learn how to remove stopwords and perform text normalization in Python — an essential Natural Language Processing (NLP) read; We will explore the different methods to remove stopwords Nov 9, 2022 · Python GateNLP is a natural language processing (NLP) and text processing framework implemented in Python. This book provides an introduction to NLP using the Python stack for practitioners. The package also contains a base class to expose a python-based annotation provider (e. Visual created by the author. Twitter provides a plethora of data that is easy to access through their API. In this tutorial, we'll learn about how to do some basic NLP in Python. It is a really powerful tool to preprocess text data for further analysis like with ML models for instance. Install and Load Main Python Libraries for NLP. So, In this article, we will discuss some of the basic concepts related to NLP. One of the most popular Python libraries for NLP is spaCy: an open-source library designed to help developers build applications that process large volumes of text with speed and efficiency at runtime, making it a good choice for building production-level NLP applications. BertSpanLabeler wraps a nlp. In particular, we will cover Latent Dirichlet Allocation (LDA): a widely used topic modelling technique. You will also learn about the different steps involved in processing the human language like Tokenization, May 14, 2023 · The goal of the Indic NLP Library is to build Python based libraries for common text processing and Natural Language Processing in Indian languages. Apr 15, 2019 · In this article, we’ll take a closer look at LDA, and implement our first topic model using the sklearn implementation in python 2. The majority of data is unstructured. Consider the string: “NLP in Python is fun and very well documented. Note that nlp. Jul 5, 2023 · 以往的自然語言處理 (Natural Language Processing, NLP)通常必先基於大量的文本資料與冗長的處理過程，而現代最新技術則是結合預訓練模型來降低自然語言處理的技術門檻，並有效提升自然語言處理的正確率與應用範圍，使得文本分群 (Text Corpus Clustering)、問答系統 Feb 12, 2020 · The pipeline of a basic QA system with a pre-trained NLP model includes two stages - preparation of data and processing as follows below: Prerequisites. Text or audio can be used to represent human languages. 1. The lists are based on our judgment and the content of the job postings. For this post we Welcome to the Practical NLP with Python course! This course is perfect for people looking for an overview of the state-of-the-art of practical NLP and what you can do with few lines of code. There Mar 3, 2022 · More From Eric Kleppen How to Practice Word2Vec for NLP Using Python Twitter API. Step #1: Loading and Cleaning the Data. Natural language processing, otherwise known as NLP, is the technology behind Siri, autocorrect, chatbots, and Google Translate. BertEncoder, the weights of which can be restored from the above pretraining Jan 3, 2024 · The provided Python code utilizes the spaCy library for natural language processing to remove stopwords from a sample text. Aug 21, 2019 · 4. g. Step #5: Matching the Keywords and the Job Descriptions. Natural Language Processing with Python Steven Bird, Ewan Klein, and Edward Loper Beijing¥ Cambridge ¥ Farnham ¥ K ln ¥ Sebastopol ¥ Taipei ¥ Tokyo Nov 23, 2020 · NLTK (Natural Language Toolkit) is the go-to API for NLP (Natural Language Processing) with Python. /venv-language. Sentiment Analysis is one of the most popular NLP techniques that involves taking a piece of text (e. See full list on towardsai. In this article, I will walk you through the traditional extractive as well as the advanced generative methods to implement Text Summarization in Python. We will learn Spacy in detail and we will also explore the uses of NLP in real life. Jan 15, 2021 · nlp = spacy. To install the library Oct 24, 2020 · Text summarization in NLP is the process of summarizing the information in large texts for quicker consumption. Part of speech tagging – Apart from the grammar relations, every word in a sentence is also associated with a part of speech (pos) tag (nouns, verbs, adjectives, adverbs etc). It’s mainly meant for beginner-to-intermediate technical people. kx pm sh jv hx zk ta do tb wb
