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Jetze Schuurmans's Projects

bsc-seminar-finance icon bsc-seminar-finance

Bachelor Seminar Quantitative Finance. A study on price volatility in the MISO electricity market. Comparing univariate and multivariate GARCH models.

bsc-seminar-qf icon bsc-seminar-qf

Bachelor Seminar Quantitative Finance. A study on price volatility in the MISO electricity market. Comparing univariate and multivariate GARCH models.

cs231n icon cs231n

CS231n Assignments Solutions - Spring 2020

dcnplus icon dcnplus

Reproducing the results of DCN+ paper submitted for ICLR 2018

e2cnn icon e2cnn

E(2)-Equivariant CNNs Library for Pytorch

ec2-instance-python icon ec2-instance-python

AWS CDK Python example of an EC2 that can be accessed by AWS System Manager and has access to S3 bucket. Configuration shell script can be provided to run on creation

hsoftmax icon hsoftmax

Implementation of Hierarchical Softmax as Global Classifier

jiraview icon jiraview

Extract data from JIRA through REST and create charts.

ml-topn-rs icon ml-topn-rs

Create a Top-N Recommender System. Starting with unsupervised learning on users. Followed by ranking function based on Random Forest and SVM. Evaluated with One-Plus-Random method.

mlifc icon mlifc

Course Material for the machine learning in financial context bootcamp

mmdetection3d icon mmdetection3d

OpenMMLab's next-generation platform for general 3D object detection.

msc-ml icon msc-ml

Group assignment for Machine Learning course. Reproducing a paper, explaining SVM, and applying SVM to a new data set.

mscthesis icon mscthesis

Master Thesis Econometrics - Intent Classification with Hierarchical and Bayesian Neural Nets

pandas icon pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

perceiver-pytorch icon perceiver-pytorch

Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch

pydataamsterdam2018 icon pydataamsterdam2018

Contents of the workshop "Hands-on introduction to Deep Learning with Keras and Tensorflow" I gave at PyData Amsterdam 2018

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