In this chapter, we’re going to cover introductory to advanced feature engineering (text to features) styles. By the end of this chapter, you’ll be comfortable with the following recipes One Hot encoding Count vectorizer N- grams Hash vectorizer Term Frequency- Inverse Document Frequency (TF- IDF) Implementing word embedding Implementing fastText Now that all the text…
1 – What is an ensemble method in NLP? Ensemble methods are a group of machine learning algorithms that work together to solve a problem. They are typically used when the machine learning algorithm is not able to solve the problem on its own or when it has not been trained enough. An ensemble method…
1 – What are some of the common NLP tasks? NLP is the process of understanding a sentence and then generating a response. It has been used in many different industries to help humans do their jobs more efficiently. Some of the common NLP tasks are: Speech recognition: This is when a computer converts spoken…
A multi-layer perceptron is a type of artificial neural network. It has one or more hidden layers between the input and output layers, each of which can be thought of as a series of processing units connected to each other in a hierarchical tree structure. The input layer nodes are connected to the hidden layer…
There are a lot of simple gradient-based NLP models that can be used to solve a variety of natural language processing tasks. Some of these include: Part-of-speech tagging: sentence parsing is a task that assigns part of speech tags to words in text and is used to analyze sentences. A task that assigns part of…
NLP is revolutionizing the way we interact with financial services. It’s allowing us to have a more natural conversation with our banks, and this is allowing us to do things that we couldn’t do before. How did you get into NLP? I got into NLP because I had a need, but it turns out that…
We are going to talk about a Natural Language Processing concept called the Bag of words model. When you’re applying an algorithm in NLP, it works with numbers and not words or sentences. We can’t feed our text directly into algorithms like that in order to analyze text data, it needs to be converted into…
Stop words are the most common words in any language that do not carry any meaning and are usually ignored by NLP. In English, examples of stop words are “a”, “and”, “the” and “of”. In NLP, stop words are typically removed from a text before it is processed for analysis. This is done to reduce…
NLP is a branch of artificial intelligence. It is used to analyze and understand human language. NLP has many applications in the real world that can be used for different purposes. Some of these applications include: Natural Language Processing (NLP) is a technique for understanding the sentiment in text. NLP can be utilized to identify…
In recent years, the blockchain has been used to track and store information on a variety of applications. It can be used to store data about transactions, contracts or other records in a secure way. Blockchain is decentralized and not controlled by any single entity. This makes it an ideal technology for machine learning algorithms.…
The blockchain is a revolutionary technology which has the potential to change how we do business. It can be used in many different fields and industries, but one of the most interesting applications is in Natural Language Processing. The blockchain has the potential to revolutionize how data is stored and shared. It can store data…
With the development of natural language processing (NLP) and machine learning, natural language processing in healthcare is becoming more and more important. NLP is a computer programming technique that uses statistical techniques to analyse text or speech and extract meaning from it. It has been used for many years in computational linguistics but only recently…