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Entity Linking & Disambiguation using REL
Entity extraction, also known as Named Entity Recognition(NER), is an information extraction process that extracts entities from unstructured text and then classifies them into predefined categories such as people, organizations, places, products, date, time, money,...
Incremental/Online/Continuous Model Training using Creme
Have you noticed the trained ML model performance degrades over time? Why will the model performance degrade? Let's say we have a model which takes the person's data as an input and detects the face. Now with the Covid situation, almost 90% of people wear masks and...
Lazy Predict – Find the best suitable ML model
As in the earlier blog “text classification using machine learning”, we saw a few drawbacks on how difficult it is to select the best ML models and time-consuming for tuning different model parameters to achieve better accuracy. To overcome this problem we will...
Text Classification with Keras and GloVe Word Embeddings
Deep Learning(DL) is the subset of Machine Learning. It is a method of statistical learning that extracts features or attributes from raw data. DL uses a network of algorithms called artificial neural networks which imitates the function of the human neural networks...
How to monitor work-flow of scraping project with Apache-Airflow
Apache Airflow is a platform to programmatically monitor workflows, schedule, and authorize projects. In this blog, we will discuss handling the workflow of scraping yelp.com with Apache Airflow. Quick setup of Airflow on ubuntu 20.04 LTS # make sure your system is...
Text Similarity using fastText Word Embeddings in Python
Text Similarity is one of the essential techniques of NLP which is used to find similarities between two chunks of text. In order to perform text similarity, word embedding techniques are used to convert chunks of text to certain dimension vectors. We also perform...
Data Cleaning using Regular Expression
Data cleaning is the process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset. The data format is not always tabular. As we are entering the era of big data, the data comes in an extensively diverse...
Build a Custom NER model using spaCy 3.0
SpaCy is an open-source python library used for Natural Language Processing(NLP). Unlike NLTK, which is widely used in research, spaCy focuses on production usage. Industrial-strength NLP spaCy is a library for advanced NLP in Python and Cython. As of now, this is the...
Stemming Vs. Lemmatization with Python NLTK
Stemming and Lemmatization are text/word normalization techniques widely used in text pre-processing. They basically reduce the words to their root form. Here is an example: Let's say you have to train the data for classification and you are choosing any vectorizer to...
Text Classification using Machine Learning
Machine Learning, Deep Learning, Artificial Intelligence are the popular buzzwords in present trends. Artificial Intelligence(AI) is the branch of computer science which deals with developing intelligence artificially to the machines which are able to think, act and...
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