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Name: (S2037987) Hii Yew Han, Joshua
Type: User
Bio: Data science learner , UM student
Name: (S2037987) Hii Yew Han, Joshua
Type: User
Bio: Data science learner , UM student
Different feature selection methods like SVD, SelectKBest, RFE are used to choose best features, then different machine learning algorithms like Random Forest, Gradient Boosting Tree, XGBoost together with GridsearchCV etc are applied and compared to choose the good model which is the best fit for the dataset.
Analytics using clickstream data and visualise it using tableau
Developed to identify at-risk students on a huge Open University Learning Analytics Dataset (OULAD) using different user patterns and filtering techniques using Python. Used Association rule to determine relationships in unrelated data. K-Means Clustering is employed to determine groups of users using Weka V-3.8.2 and bring insights on the data.
A topic-centric list of HQ open datasets.
Learning the impact of Learning Analytics with an authentic dataset
This repository contains Python file and presentation for OULAD
Mining clickstream data to predict if a visitor will view another page or leave the website.
E-Commerce | Binary Classification | User Behavior Analysis| Logistic Regression | Random Forest | Light GBM|Neural Net|KNN |Python (scikitlearn, seaborn, pandas, numpy, matplotlib)
Analyzing Clickstream Data using Markov Chains and data mining SPACE algorithm
Deep learning using Recurrent Neural Networks on student code submissions; focusing on LSTMs to predict student success
A collection of various deep learning architectures, models, and tips
In the beginning, the algorithm chooses k centroids in the dataset randomly after shuffling the data. Then it calculates the distance of each point to each centroid using the euclidean distance calculation method.
Tutorials on Python programming, data analysis, data visualizations and tech career advice
In this project, we predicted if the Falcon 9 first stage will land successfully by following the data science methodology. We also summarized the results for the business stakeholders.
Machine Learning, Time Series & Survival Analysis. Develop working skills in the main areas of Machine Learning: Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning. Also gain practice in specialized topics such as Time Series Analysis and Survival Analysis.
Keras documentation, hosted live at keras.io
Evaluating the performance of hand crafted features that aim to capture higher level leaner properties for dropout prediction for a final year Learning Analytics module
This is an LSTM stock prediction using Tensorflow with Keras on top.
2nd Year: 1st - 92. A brief project and report on using the OULAD data set to predict and return a CSV of students final grades, from a variety of features, using a Random Forest or an SVC.
BEST SCORE ON KAGGLE SO FAR. Mean Square Error after repeated tuning 0.00032. Used stacked GRU + LSTM layers with optimized architecture, learning rate and batch size for best model performance. The graphs are self explanatory once you click and go inside !!!
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.