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Seungjun (Josh) Kim
Seungjun (Josh) Kim

348 Followers

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Published in

Geek Culture

·Jul 10

What is Generative AI? Overview in Simple Language for Non-Experts

Beginner friendly overview of what Generative AI is and what the hype nowadays is all about — News about Large Language Models (LLMs) are hot potatoes in any field. Even in fields that people would view as irrelevant from technology, various ways to incorporate LLMs into their workflow or operations are being actively discussed. LLMs such as ChatGPT from OpenAI is one example of Generative Artificial Intelligence…

Generative Ai

7 min read

What is Generative AI? Overview in Simple Language for Non-Experts
What is Generative AI? Overview in Simple Language for Non-Experts
Generative Ai

7 min read


Published in

Python in Plain English

·Apr 27

Semi-Supervised Learning: Label Spreading for Classification

Beginner friendly tutorial for understanding what label Spreading for semi-supervised learning is and learn how to use it for both tabular and text data — Introduction What is semi-supervised learning? As the name suggests, semi-supervised learning lies somewhere between supervised and unsupervised learning. Supervised learning in machine learning refers to the classical models we encounter where we have training data each data point labeled (in a classification problem setting) and a model is trained using that…

Semi Supervised Learning

8 min read

Semi-Supervised Learning: Label Spreading for Classification
Semi-Supervised Learning: Label Spreading for Classification
Semi Supervised Learning

8 min read


Published in

Geek Culture

·Apr 19

Semi-Supervised Learning: Label Propagation for Classification

Beginner friendly tutorial for understanding what label propagation for semi-supervised learning is and learn how to use it for both tabular and text data — Introduction What is semi-supervised learning? As the name suggests, semi-supervised learning lies somewhere between supervised and unsupervised learning. Supervised learning in machine learning refers to the classical models we encounter where we have training data each data point labeled (in a classification problem setting) and a model is trained using that…

Semi Supervised Learning

7 min read

Semi-Supervised Learning: Label Propagation for Classification
Semi-Supervised Learning: Label Propagation for Classification
Semi Supervised Learning

7 min read


Published in

Geek Culture

·Mar 2

Introduction to the medspaCy, the medical Named Entity Recognition(NER) package

Take a look at the medspaCy Python package, an open source package effective for performing various NLP tasks when ti comes to medical and health related text data. — Introduction Named Entity Recognition (NER) is a kind of Natural Language Processing (NLP) task that tags entities in text with their corresponding type. Many algorithms and open source packages that implemented them are already available for data scientists and researchers to use. One such example would be Python’s SpaCy package. However…

NLP

5 min read

Introduction to the medspaCy, the medical Named Entity Recognition(NER) package
Introduction to the medspaCy, the medical Named Entity Recognition(NER) package
NLP

5 min read


Published in

Geek Culture

·Dec 24, 2022

Let us Extract some Topics from Text Data — Part V: Top2Vec

Learn about the SOTA model for topic modeling — Introduction Topic modeling is a type of Natural Language Processing (NLP) task that utilizes unsupervised learning methods to extract out the main topics of some text data we deal with. The word “Unsupervised” here means that there are no training data that have associated topic labels. …

NLP

10 min read

Let us Extract some Topics from Text Data — Part V: Top2Vec
Let us Extract some Topics from Text Data — Part V: Top2Vec
NLP

10 min read


Published in

Towards Data Science

·Dec 19, 2022

Let us Extract some Topics from Text Data — Part IV: BERTopic

Learn more about the family member of BERT for topic modelling — Introduction Topic modeling is a type of Natural Language Processing (NLP) task that utilizes unsupervised learning methods to extract out the main topics of some text data we deal with. The word “Unsupervised” here means that there are no training data that have associated topic labels. …

NLP

10 min read

Let us Extract some Topics from Text Data — Part IV: BERTopic
Let us Extract some Topics from Text Data — Part IV: BERTopic
NLP

10 min read


Published in

Towards Data Science

·Dec 14, 2022

Let us Extract some Topics from Text Data — Part III: Non-Negative Matrix Factorization (NMF)

Learn more about the unsupervised algorithm derived from linear algebra that uses an intuitive approach to topic modelling — Introduction Topic modeling is a type of Natural Language Processing (NLP) task that utilizes unsupervised learning methods to extract out the main topics of some text data we deal with. The word “Unsupervised” here means that there are no training data that have associated topic labels. …

NLP

10 min read

Let us Extract some Topics from Text Data — Part III: Non-Negative Matrix Factorization (NMF)
Let us Extract some Topics from Text Data — Part III: Non-Negative Matrix Factorization (NMF)
NLP

10 min read


Published in

Geek Culture

·Nov 7, 2022

Let us Extract some Topics from Text Data — Part II: Gibbs Sampling Dirichlet Multinomial Mixture (GSDMM)

Learn how to use GSDMM for Topic Modeling and how it compares to LDA — Introduction In the previous article of this topic modeling series, I introduced you one of the most popular and widely used topic modeling algorithm called Latent Dirichlet Allocation (LDA). Take a look at it in the following link! Let us Extract some Topics from Text Data — Part I: Latent Dirichlet Allocation (LDA) Learn what topic modelling entails and its implementation using Python’s nltk, gensim, sklearn, and pyLDAvis packagestowardsdatascience.com

Topic Modeling

9 min read

Let us Extract some Topics from Text Data — Part II: Gibbs Sampling Dirichlet Multinomial Mixture…
Let us Extract some Topics from Text Data — Part II: Gibbs Sampling Dirichlet Multinomial Mixture…
Topic Modeling

9 min read


Published in

Towards Data Science

·Nov 3, 2022

Let us Extract some Topics from Text Data — Part I: Latent Dirichlet Allocation (LDA)

Learn what topic modelling entails and its implementation using Python’s nltk, gensim, sklearn, and pyLDAvis packages — Introduction Topic modeling is a type of Natural Language Processing (NLP) task that utilizes unsupervised learning methods to extract out the main topics of some text data we deal with. The word “Unsupervised” here means that there are no training data that have associated topic labels. …

Topic Modeling

12 min read

Let us Extract some Topics from Text Data — Part I: Latent Dirichlet Allocation (LDA)
Let us Extract some Topics from Text Data — Part I: Latent Dirichlet Allocation (LDA)
Topic Modeling

12 min read


Published in

Geek Culture

·Oct 31, 2022

The Ultimate NLP Mind Map to Have

Overview of all the components of NLP Analysis in a nutshell — Introduction Natural Language Processing (NLP) is a gigantic field that encompasses various components from cleaning, lemmatization, stemming to deep learning models for text classification and State-of-the-Art (SOTA) pre-trained language models for advanced tasks such as summarization, text generation and sentiment analysis. …

NLP

8 min read

The Ultimate NLP Mind Map to Have
The Ultimate NLP Mind Map to Have
NLP

8 min read

Seungjun (Josh) Kim

Seungjun (Josh) Kim

348 Followers

Data Scientist; PhD Student in Informatics; Artist (Singing, Percussion); Consider Supporting Me : ) https://joshnjuny.medium.com/membership

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