TOPBOTS

The Best of Applied Artificial Intelligence, Machine Learning, Automation, Bots, Chatbots

NLP Tutorials

Topical Language Generation With Transformers

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Full PaperCodesLarge-scale transformer-based language models (LMs) demonstrate impressive capabilities in open text generation. However, controlling the generated text’s properties such as the topic, style, and sentiment is challenging and often requires significant changes to the model architecture or retraining and fine-tuning the model on new supervised data.We … [Read more...] about Topical Language Generation With Transformers

To ROUGE Or Not To ROUGE?

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In this article, we will learn about …… the difference between extractive and abstractive text summarization.… what the ROUGE score is.… why and where it fails.Text SummarizationWe refer to text summarization as the process of training an Artificial Intelligence (AI) model to produce a smaller chunk of text out of a bigger chunk of text. Where “smaller … [Read more...] about To ROUGE Or Not To ROUGE?

BERT Inner Workings

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I created this notebook to better understand the inner workings of Bert. I followed a lot of tutorials to try to understand the architecture, but I was never able to really understand what was happening under the hood. For me it always helps to see the actual code instead of just simple abstract diagrams that a lot of times don’t match the actual implementation. If you’re like … [Read more...] about BERT Inner Workings

GPT2 For Text Classification Using Hugging Face Transformers

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This notebook is used to fine-tune GPT2 model for text classification using Hugging Face transformers library on a custom dataset.Hugging Face is very nice to us to include all the functionality needed for GPT2 to be used in classification tasks. Thank you Hugging Face!I wasn’t able to find much information on how to use GPT2 for classification so I … [Read more...] about GPT2 For Text Classification Using Hugging Face Transformers

Extractive Text Summarization Using Contextual Embeddings

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Text Summarization is a process of generating a compact and meaningful synopsis from a huge volume of text. Sources for such text include news articles, blogs, social media posts, all kinds of documentation, and many more. If you are new to NLP and want to read more about text summarization, this article will help you understand the basic and advanced concepts. The … [Read more...] about Extractive Text Summarization Using Contextual Embeddings

From Text to Knowledge: The Information Extraction Pipeline

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I am thrilled to present my latest project I have been working on. In this blog post, I will present my implementation of an information extraction data pipeline, following my passion for combining natural language processing and knowledge graphs. Later on, I will also explain why I see the combination of NLP and graphs as one of the paths to explainable AI.If this in-depth … [Read more...] about From Text to Knowledge: The Information Extraction Pipeline

Building a Complete AI Based Search Engine with Elasticsearch, Kubeflow and Katib

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Building search systems is hard. Preparing them to work with machine learning is really hard. Developing a complete search engine framework integrated with AI is really really hard.So let’s make one. ✌️In this post, we’ll build a search engine from scratch and discuss on how to further optimize results by adding a machine learning layer using Kubeflow and Katib. This … [Read more...] about Building a Complete AI Based Search Engine with Elasticsearch, Kubeflow and Katib

Natural Language Processing in Production: 27 Fast Text Pre-Processing Methods

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Estimates state that 70%–85% of the world’s data is text (unstructured data) [1]. New deep learning language models (transformers) have caused explosive growth in industry applications [5,6,11].This blog is not an article introducing you to Natural Language Processing. Instead, it assumes you are familiar with noise reduction and normalization of text. It covers … [Read more...] about Natural Language Processing in Production: 27 Fast Text Pre-Processing Methods

The Relationship Between Perplexity And Entropy In NLP

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Perplexity is a common metric to use when evaluating language models. For example, scikit-learn’s implementation of Latent Dirichlet Allocation (a topic-modeling algorithm) includes perplexity as a built-in metric.In this post, I will define perplexity and then discuss entropy, the relation between the two, and how it arises naturally in natural language … [Read more...] about The Relationship Between Perplexity And Entropy In NLP

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