Embedded Files
Natural Language Processing
Natural Language Processing
IDE: Jupyter Notebook
--> Extracted tokens,
Processed Named Entity Recognition (NER) , according to SpaCy and displaCy libraries
---> Utilized Spans, "like_num", "is_alpha", "is_punct" to check properties of token
---> Conducted Sentiment Analysis to obtain subjectivity and polarity scores based on the certain tokens
---> Analyze natural language messages based on scoring and use scores to predict word trendency reversely
Network Analysis
Network Analysis
------------------------------------------------------------------->
Counted the weighed average degrees, between centrality, and min / max degrees of paths (between one node and the other)
Interpreted practical implications and apply those values into real world scenarios (e.g., Pre-planning for most cost effective tourist path)
.........
imported networkx lib to create networks base on the df.
used matplotlib to visualize networks
analyzed the network plot charts based on the nodes, edges, highest/lowest weighted degrees
......
Language model
Language model
deployment
deployment
Applied Natural language process and machine learning knowledge to deploy a simple language model for DP Breath service design.
Learning more about :
Machine Learning, Deep Learning, decision trees, neural networks .....
Using Hugging Face, Tensorflow to deploy pre-trained models
DP Breath 1st generation Chatbot
Using Google AI Studio API key to fine tine model temperature and other parameters, adapt into various project working scenarios
Learning and Training model using Google Colab cloud based IDE to setup libraries of Tensorflow, PyTorch, NumPy ...
Executing python codes to dive deeper into machine learning field
geocoding, locating in python 🌍
geocoding, locating in python 🌍
geocode specific locations to access information of locations' latitudes, longitudes and importance scores...
use folium library to create and mark location on maps
Page updated
Google Sites
Report abuse