Experiments with different ML techniques using TensorFlow and Sci-kit-learn in Python
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Mar 24, 2017 - Jupyter Notebook
Experiments with different ML techniques using TensorFlow and Sci-kit-learn in Python
Exploring pretrained Word2Vec for analysis of Metadata Keywords
Notebook on NLP basics - NLP pipeline, different word embeddings and LDA
This project has two parts: in one notebook we analyzed word embeddings that were trained on songs of various genres while the other notebook trains a lyric generation model.
Contains relevant notebooks for the hands-on NLP workshop by organized Analytics India Magazine Plugin Conference-2020 Edition
Repository for R Markdown Notebook containing codes for the paper "vector space models and the usage patterns of Indonesian denominal verbs" (published in NUSA)
Word2Vec is a popular word embedding technique that converts words into vectors in a high-dimensional space, capturing semantic relationships between words. This notebook demonstrates embedding text data with Word2Vec for sentiment analysis.
A notebook that contains a collection of NLP models that automatically score essays
Portfolio Project.ipynb and Recommendation.py are the finalized Jupiter notebook scripts for this project. Other files are a work in progress to migrate into a web app.
Notebooks of programming assignments of Sequence Models course of deeplearning.ai on coursera in May-2020
Workshop on Machine Learning in production for Statistics and Information Management course
Collection of Jupyter Notebooks with examples of NLP models.
A place to find all basic old school Deep Learning concepts, codes and Google Colab trainable python notebooks.
Jupyter notebooks for the Deep Learning course that is held at FEI, VSB-TU Ostrava
Global vector modelling notebooks for Ancient Greek
This repo contains the codes and the notebooks used for the paper "Exploring Temporal GNN Embeddings for Darknet Traffic Analysis".
In this notebook, I am updating NLP notebooks, and projects
A scientific benchmark and comparison of the performance of sentiment analysis models in NLP on small to medium datasets
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