changshuren

Advanced-Regression

Advanced_Data_Science_with_IBM

This is the repository for the Advanced Data Science with IBM Specialization in Coursera

Advanced_Regression_House_Price_Prediction

Build a mode that can help best predict house prices based on 186 factors.

Anomaly-Detection-via-PyCaret

Automatic_Ticket_Classification_Project

awesome-seml

A curated list of articles that cover the software engineering best practices for building machine learning applications.

Breast-Cancer-Classifications

Capstone_Project_Credit_Card_Fraud_Detetction

Credit Card Fraud Detetction Project By Shu-Ren Chang

Data-Science-ML-Full-Stack-2022

Everything you need to know for data science.

NLP_Syntactic_Processing

Syntactic Processing techniques include: 1. PoS tagging and HMM model; 2. Constituency and Dependency parsing; 3. Name Entity Recognition (NER); 4. Custom NER and Conditional Random Fields (CRF); and 5. Application of each topic in Python using Spacy library.

changshuren/NLP_Syntactic_Processing

Syntactic Processing techniques include: 1. PoS tagging and HMM model; 2. Constituency and Dependency parsing; 3. Name Entity Recognition (NER); 4. Custom NER and Conditional Random Fields (CRF); and 5. Application of each topic in Python using Spacy library.

changshuren/Advanced-Regression

changshuren/Automatic_Ticket_Classification_Project

changshuren/Capstone_Project_Credit_Card_Fraud_Detetction

Credit Card Fraud Detetction Project By Shu-Ren Chang

changshuren/Classifying-Skin-Cancer-Melanoma-using-Convolutional-Neural-Networks

Classifying Skin Cancer (Melanoma) using Convolutional Neural Networks

changshuren/Convolutional-Neural-Networks

changshuren/Cross-Validation-for-Linear-Regression-for-House-Prices

This notebook demonstrates how to do cross-validation (CV) for linear regression with `sklearn`. This technique is commonly used in almost all modelling in decision trees, SVM etc.

changshuren/Climate-Change

changshuren/Hand-Gesture-Recognition-with-CNN-and-RNN

In this project, the task is to build a 3D Conv model that will be able to predict the 5 gestures correctly.

changshuren/linux

Linux kernel source tree

changshuren/MLOps-NLP-Case-Study-Architecture-Design-for-Development-and-Production-Environments

This case study, authored by Shu-Ren Chang, Ph.D. explores MLOps in the context of NLP analytics. It includes the design of an MLOps architecture tailored for both development and production environments.

changshuren/MLOps_Clean_Coding_Principles

changshuren/MLOps_Convert_Notebooks_to_Scripts

changshuren/MLOps_Exception_Handling_and_Logging

changshuren/Mlops_Lead_Scoring_for_Code_Pro_EduTech

changshuren/MLOps_Unit_Test

changshuren/NLP_01_Intro_Lexical_Processing_Python_Practice

changshuren/NLP_02_Baisc_Lexical_Processing_Python_Practice

changshuren/NLP_03_Advanced_Lexical_Processing_Python_Practice

changshuren/NLP_Lexcial_Processing

The demoed Lexical Process in Natural Language Procession includes regular expressions, tokenization, stemming, lemmatization, TF-IDF model, phonetic hashing, and minimum edit distance algorithm.

changshuren/NLP_Pipeline-Hugging-Face-offers-Transformer-library-API

Hugging Face offers the Transformer library API for NLP models. Pipelines are a great and easy way to use all types of models for inference. These pipelines offers a simple API dedicated to several tasks, including named entity recognition, masked language modelling, sentiment analysis, feature extraction, and question answering.

changshuren/NLP_Semantic_Processing

Semantic processing is the most challenging area in the field of NLP because it is difficult to let machines understand the text the same way as human do such as inferring the intent, distinguishing ambiguity of words, dealing with synonyms, detecting sarcasm, etc.

changshuren/NLP_Syntactic_Processing_for_Medical_Data_with_NER_CRF_using_SpaCy

This project aims to identify disease names along with treatment plans to help physicians arrange better treatments. The textual extraction technique: Name Entity Recognition (NER), CRF (Conditional Random Field) classifier, Random Forest Classifier, and HMM (Hidden Markov Model) are used to identify the entities like Disease and Treatment.

changshuren/Penn_GSE_DSMDLP

changshuren/Regular_Expressions_Practice

Regular expressions are very powerful tool in text processing that help clean and handle textual analysis more efficiently.

changshuren/Regular_Expressions_Questions_only

changshuren/Regular_Expressions_Questions_with_Solutions

changshuren/Sentiment-Analysis-for-Movie_Reviews_using_Bernoulli_Naive_Bayes

A Multinomial Naive Bayes classification model was built and trained in Python to predict the accuracy.

changshuren/Text_Encoding_for_ASCII_Unicode

changshuren/UTF-8_Encoder-Decoder_for_String

This coding is used as encoder-decoder for string for UTF-8, UTF-16, and UTF-32 codes