Overcoming the Limitations of Large Language Models
How to enhance LLMs with human-like cognitive skills- 20586Murphy ≡ DeepGuide
Uncovering the Pioneering Journey of Word2Vec and the State of AI science – an in-depth interv
In 2012, Dr Tomas Mikolov received his PhD in Artificial Intelligence at the Brno University of Technology in the Czech Republic with a...- 21188Murphy ≡ DeepGuide
Writing a book on NLP is a bit like solving a complex data science project
An interview with Lewis Tunstall, co-author of the book- Natural Language Processing with Transformers- 28666Murphy ≡ DeepGuide
Intermediate Deep Learning with Transfer Learning
Getting started with Deep Learning is easy. You can have a neural network setup and training within just a few lines of code. But it can become overwhelming when you go from a beginner to an intermediate level. You are confronted with many new terms like- 25400Murphy ≡ DeepGuide
Quick Text Sentiment Analysis with R
Use TidyText to create a nice and quick text analysis with R- 23765Murphy ≡ DeepGuide
A Decade of Knowledge Graphs in Natural Language Processing
An overview of the research landscape combining structured and unstructured knowledge in NLP- 21564Murphy ≡ DeepGuide
Improving Hebrew Q&A Models via Prompting
Using the OpenAI API and Pinecone DB- 24390Murphy ≡ DeepGuide
A Recommendation System For Academic Research (And Other Data Types)!
Implementing Natural Language Processing and Graph Theory to compare and recommend different types of documents- 20309Murphy ≡ DeepGuide
Public Benchmarks for Medical Natural Language Processing
A general introduction to a list of canonical tasks and corresponding datasets to measure your medical natural language processing- 30092Murphy ≡ DeepGuide
How to Leverage Pre-Trained Transformer Models for Custom Text Categorisation?
So, you have some custom text dataset that you wish to categorise, but wondering how? Well, let me show you how, using pre-trained state...- 27451Murphy ≡ DeepGuide
How Few-Shot Learning is Automating Document Labeling
Leveraging GPT Model- 21765Murphy ≡ DeepGuide
Are Prompts Generated by Large Language Models (LLMs) Reliable?
Unleashing the Power of LLMs with Auto-Generated Prompts- 29163Murphy ≡ DeepGuide
Can ChatGPT Compete with Domain-Specific Sentiment Analysis Machine Learning Models?
A hands-on comparison using ChatGPT and Domain-Specific Model- 27407Murphy ≡ DeepGuide
The Case Against Enterprise LLMs
A sober perspective as to why boring is best, even for AI- 22862Murphy ≡ DeepGuide
What People Write about Climate: Twitter Data Clustering in Python
Clustering of Twitter data with K-Means, TF-IDF, Word2Vec, and Sentence-BERT- 26814Murphy ≡ DeepGuide
ChatGPT Generated Food Industry Reviews: Realism Assessment
Where It Started The bulk of my research in the past used Generative Adversarial Networks (GAN) for creating deepfake images of my dataset. I wanted to do this to increase the diversity of information within my dataset, which I predicted would result in b- 26611Murphy ≡ DeepGuide
How to automate entity extraction from PDF using LLMs
Leveraging zero-shot labeling- 29948Murphy ≡ DeepGuide
GPT vs BERT: Which is Better?
Comparing two large-language models: Approach and example- 24417Murphy ≡ DeepGuide
How Generative AI Can Support Food Industry Businesses
Introduction The journey I am about to take you on is important for two reasons. It will show you how you can use ChatGPT to help support companies working in the food industry. Arguably the most important reason, I am going to walk through a post I made- 28739Murphy ≡ DeepGuide
Inside GPT – I : Understanding the text generation
A simple explanation to the model behind ChatGPT- 24612Murphy ≡ DeepGuide
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We look at an implementation of the HyperLogLog cardinality estimati
Using clustering algorithms such as K-means is one of the most popul
Level up Your Data Game by Mastering These 4 Skills
Learn how to create an object-oriented approach to compare and evalu
When I was a beginner using Kubernetes, my main concern was getting
Tutorial and theory on how to carry out forecasts with moving averag