Consumer Complaint Classification means classifying the nature of the complaint reported by the consumer. It is helpful for consumer care departments as they receive thousands of complaints daily, so classifying them helps identify complaints that need to be solved firstā¦
Grammarly is one of the best examples of applications that use Machine Learning for their business. Grammarly helps write a text for any purpose and uses Machine Learning to make that text more readable and engaging. So, if you wantā¦
Natural Language Processing (NLP) is a subset of Artificial Intelligence where we aim to train computers to understand human languages. Some real-world applications of NLP are chatbots, Siri, and Google Translator. While working on any problem based on NLP, weā¦
Text generation involves generating text using machine learning techniques. The purpose of text generation is to automatically generate text that is indistinguishable from a text written by a human. If you want to learn how to generate text with Python,ā¦
Natural language processing (NLP) is a subfield of artificial intelligence and computer science. NLP is the process of processing and analyzing natural language data to create intelligent applications that can understand human languages. Like machine learning, Python is also preferredā¦
Text classification is a machine learning technique used to classify texts based on predefined labels. For example, classifying languages based on a dataset containing different languages with predefined labels. Text classification is used in various problems of natural language processingā¦
Tokenization is the first step you should perform after collecting a textual dataset in every problem based on Natural Language Processing. Sentence and Word tokenization are two different strategies of tokenization that you should know. In this article, I willā¦
Language detection is a natural language processing task where we need to identify the language of a text or document. Using machine learning for language identification was a difficult task a few years ago because there was not a lotā¦
One of the common tasks in natural language processing is sentiment analysis. If you want to work on a project based on natural language processing, sentiment analysis will be a good choice. Before you start a project on sentiment analysis,ā¦
The NLTK library in Python is one of the best Python libraries for any natural language processing task. It provides so many useful functions for word processing including tokenization, stemming, tagging, parsing and many other tasks that we need toā¦
The task of language detection comes into use when you are working on a very large dataset that contains data in different languages. Suppose you want to create an even driven program where the final output depends on the languageā¦
Language translator is one of those apps that helped me a lot while studying the German language during my graduation. Google Translator API helps us to create our translator using Python. In this article, I will walk you through howā¦
Stop Words removal is an important step while working on any application of natural language processing. Stop Words are words that carry very little or no significant semantic context in a piece of text which is why such words needā¦
A Chatbot is an application that interacts with users like a human. Chatbots are typically used to resolve the most common queries that a business receives from its customers daily. In this article, I’ll walk you through how to createā¦
Natural Language Processing or NLP is the field of Artificial Intelligence that empowers a computer system to read and understand human languages. In this article, I will take you through a complete roadmap on how to learn Natural Language Processing.ā¦
Natural Language Processing (NLP) is the field of Artificial Intelligence which means to train a computer system or any machine to understand human languages. NLTK and spaCy are two of the most used Python packages for the tasks of NLP.ā¦
Using correct grammar is very important in any language. The role that syntax plays in a programming language is what grammar plays in any language. In this article, I will walk you through the grammar correction task using Python. Howā¦
A human can express his emotions in any form, such as face, gestures, speech and text. The detection of text emotions is a content-based classification problem. In this article, I will take you through how to solve the problem ofā¦
Keywords play an important role when reading a long text to understand the subject and context of the text. Search engines also analyze an article’s keywords before indexing it. In this article, I will walk you through how to extractā¦
You must therefore have seen the prediction of the next word on the keyboard of our smartphones which is most of the time precise. How does our keyboard predict the next word? In this article, I will walk you throughā¦
Text Summarization is the process of creating a summary of a certain document which contains the most important information of the original, the purpose of which is to obtain a summary of the main points of the document. In thisā¦
Have you ever thought about how the autocorrect features works in the keyboard of a smartphone? Almost every smartphone brand irrespective of its price provides an autocorrect feature in their keyboards today. So let’s understand how the autocorrect features works.ā¦
In this article, I will take you through how we can predict the US presidential elections with Python. Here, I will not train any machine learning model. I will analyze the sentiments of people for the candidates and then atā¦
Natural Language Processing (NLP) consists of developing applications and services capable of understanding human languages. Some practical examples of NLP are speech recognition, for example, Google voice search, understanding content or analyzing feelings, etc. In this article, I will takeā¦
Word embeddings or word vectors represent each word numerically so that the vector matches how that word is used or what it means. Vector encodings are learned by considering the context in which the words appear. Words that appear inā¦
Natural Language Processing (NLP) is a great task in Machine Learning to work with languages. However, you must have seen everyone working with only in the English language while working on a task of NLP. So what about other languagesā¦
Text Summarization involves condensing a piece of text into a shorter version, reducing the size of the original text while preserving key information and the meaning of the content. Since manual text synthesis is a long and generally laborious task,ā¦
In Machine Learning, the Stemming process is widely used in tagging, indexing, SEO, web search results and information search. For example, the search for fish on Google will also result in fish, fishing as fish is the root of theā¦
The term hate speech is understood as any type of verbal, written or behavioural communication that attacks or uses derogatory or discriminatory language against a person or group based on what they are, in other words, based on their religion,ā¦
Text to speech is the generation of speech synthesized from the text. The technology is used to communicate with users when reading a screen is not possible or impractical. This not only opens up apps and information to use inā¦
Natural Language Processing (NLP) consists of developing applications and services capable of understanding human languages. Some practical examples of NLP are speech recognition, for example, Google voice search, understanding content or analyzing feelings, etc. Use of Natural Language Processing (NLP)ā¦
Have you ever tried to translate any text using google, it’s straightforward and helpful to do so when I used to study the German Language google helped me alot in my homework. Do you know how Google does that? Googleā¦
Named Entity means anything that is a real-world object such as a person, a place, any organisation, any product which has a name. For example – “My name is Aman, and I and a Machine Learning Trainer”. In this sentenceā¦
Audio Feature Extraction has been one of the significant focus of Machine Learning over the years. The most frequent common state of data is a text where we can perform feature extraction quite smoothly. Then we have Feature Extraction forā¦
I recently shared an article on Audio Processing with Python. It was about how you can process and manipulate an audio file with Python. If you have gone through that, now you must know about how the basic stuff ofā¦