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Predicting Students' Dropout and Academic Success via Classification
I used KNN, SVM, SGDClassifier and Random Forest to classify student data in order to identify who will graduate, drop out or stay enrolled. The report of this project can be found at https://github.com/betulmesci/classification-of-students/blob/main/Classification_final.pdf
Predicting Stock Prices of Home Depot Based on Trends and the Sentiment of News and Tweets
In this project, I applied Linear Regression and CNN+LSTM on Home Depot's historical stock price data. I gathered tweets and Google news results related to Home Depot and ran sentiment analysis on them. I also incorporated the number of Google searches of Home Depot (trends). I applied Linear Regression and CNN+LSTM on the historical + sentiment + trends data. Finally, I applied K-Means clustering and incorporated that information in the data as well and ran the same analysis. The models, especially CNN+LSTM, could predict the target variable almost perfectly.
Image Processing Tutorial Using scikit-image - Image Segmentation
In this section, I talked about two kinds of image segmentation techniques: Supervised and Unsupervised. For Supervised method, I explored Active Contour and Random Walker methods to detect the face of a person. For Unsupervised method, Simple Linear Iterative Clustering (SLIC) and Felzenszwalb Clustering techniques were discussed.
DeepWalk is a type of graph neural network that uses language model to learn latent representations of vertices in a network. DeepWalk includes two main components: Firstly, it uses random walk to infer main local components in the graph. Secondly, it uses SkipGram algorithm to train parameters for embeddings.
FINAL PROJECT 1: LINEAR REGRESSION
LUKMAN PRASETYO NUGROHO (PYTN-KS09-004) NATHANIA GUNAWAN (PYTN-KS09-006) Dataset yang kami gunakan yaitu Uber and Lyft Dataset Boston, MA yang berisi histori data perjalanan Uber dan Lyft di Boston. Analisis kami bertujuan untuk memprediksi dan membandingkan, Bagaimana cab type, name, surge multiplier, dan distance mempengaruhi harga Uber dan Lyft.