Thanapoom Phatthanaphan's repositories
CS584_Natural-Language-Processing
Learned knowledge and techniques in Natural Language Processing and also related tools: Python, Pytorch, Jupyter Notebook, Google Colab, RNN, CNN, Reinforcement Learning, LSTM, Language Modeling
Telecom-Customer-Churn-Predictions
Developed a churn prediction classification model using various techniques including: EDA, Decision trees, Naive Bayes, AdaBoost, MLP, Bagging, RF, KNN, logistic regression, SVM, Hyperparameter tuning using Grid Search CV and Randomized Search CV.
CS541_Artificial-Intelligence
Learned both learning and problem solving to develop statistical models for real-world AI applications
CS556_Mathematical-Foundations-Machine-Learning
Learned the fundamentals of mathematic and some techniques in machine learning: Linear Algebra, Calculus, Probability, Linear Regression, Support Vector Machine
Movies-Recommendation-Hybrid-System
Developed a Hybrid movies recommendation system, using various techniques including: Collaborative Filtering, Content-Based Filtering, Singular Value Decomposition, Min-Max Normalization, Cosine Similarity, Linear Regression Model
CS513_Knowledge-Discovery-Data-Mining
Learned techniques and tools for Knowledge Discovery and Data Mining: R, RStudio, Classification Models
CS561_Database-Management-System-I
Learned the fundamental concepts of database management systems, emphasizing relational databases in both theory and practice.
CS570_DataStructures-Algorithms
Learned Data Structures and Algorithms: Basic Programming Constructs, Data types, Search trees, Hashing, Complexity Analysis, Algorithm design, Graph algorithms, Sort algorithms
BERT-Sentiment-Analysis-Bank-Customers-Reviews
Developed a sentiment analysis using BERT to analyze each customer review to judge that it is positive or negative review.
BIA660_Web-Mining
Learned techniques and tools for Web Mining and Natural Language Processing: BeautifulSoup, Selenium, Regular Expression, Text Classification, Text Clustering
CS501_Introduction-Java-Programming
Learned basic Java Programming: Data types, Flow of control, Classes, Methods and Objects, Arrays, Exception Handling, and Recursion.
CS515_Fundamentals-Computing
Learned basic Python programming: Program design, Algorithmic thinking, Recursion, Object-oriented programming, Interpreters, Compilers, and Data representation
CS550_Computer-Organization-Programming
Learned Computer organization and Assembly programming: Structure of program computer, Linking and Loading, Translation of high-level language, Logic design, Processor design, Data path, Hardwired control, Microprogrammed control
CS559_Machine-Learning-Fundamentals-Applications
Learned the fundamentals and applications in ML: Intro to Prob. & Linear algebra, Decision Theory, MLE & BE, Linear Model, Linear Discriminant function, Perceptron, FLD, PCA, Non-parametric Learning, Clustering, EM, GMM, EM and Latent Variable Model, Probabilistic Graphical Model, Bayesian Network, Neural Network, SVM, Decision Tree and Boosting
CS583_Deep-Learning
Learned knowledge and techniques in Deep Learning and also related tools: Python, Pytorch, Jupyter Notebook, RNN, CNN, Reinforcement Learning, LSTM, BERT, Language Modeling
Skills-Requirements-Analysis-using-NLP
Analyzed the job descriptions of the data analyst roles on Indeed website using Python and NLP to present the top required skills for the data analyst positions.