valdanchev
Lecturer (Assistant Professor) in Business Analytics at Queen Mary University of London and a Fellow of the Software Sustainability Institute
Queen Mary University of London, School of Business and ManagementUK
Pinned Repositories
ArtofStatistics
Code for 'The Art of Statistics'
Automated_Replications_Literature
Automated Replications: Scalable, Rapid, and Updating — Crowdsourcing of Literature
awesome-jupyter
A curated list of awesome Jupyter projects, libraries and resources
BITSS2016
dynamic-documents-with-jupyter-notebook
Dynamic documents with Jupyter Notebook for reproducible workflows
practical-statistics-for-data-scientists
Code repository for O'Reilly book
reproducible-data-science-python
Reproducible Data Science with Python
SC207
valdanchev.github.io
Repository for my personal webpage https://valdanchev.github.io
valdanchev's Repositories
valdanchev/reproducible-data-science-python
Reproducible Data Science with Python
valdanchev/dynamic-documents-with-jupyter-notebook
Dynamic documents with Jupyter Notebook for reproducible workflows
valdanchev/practical-statistics-for-data-scientists
Code repository for O'Reilly book
valdanchev/SC207
valdanchev/valdanchev.github.io
Repository for my personal webpage https://valdanchev.github.io
valdanchev/ArtofStatistics
Code for 'The Art of Statistics'
valdanchev/Automated_Replications_Literature
Automated Replications: Scalable, Rapid, and Updating — Crowdsourcing of Literature
valdanchev/awesome-jupyter
A curated list of awesome Jupyter projects, libraries and resources
valdanchev/BITSS2016
valdanchev/connected-nx-tutorial
Repository for code and notebooks for the a NetworkX Tutorial
valdanchev/CW22
Lightning talk presentation for Collaborations Workshop 2022 (CW22) https://www.software.ac.uk/cw22
valdanchev/data-science-a-first-intro-worksheets
Worksheets to accompany Data Science: A First Introduction
valdanchev/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
valdanchev/doi-demo-notebook
Demo notebook with DOI data access and interactive plotting
valdanchev/Game-Theory-and-Python
Game Theory and Python, a workshop investigating repeated games using the prisoner's dilemma
valdanchev/gds18
Geographic Data Science'18
valdanchev/gh-syllabus
A template for a gh-pages hosted syllabus
valdanchev/InteractiveBinPacking
Self-guided tutorial on combinatorial optimization, the bin packing problem, and constructive heuristics, suitable for use as course assignments, or by self-directed learners.
valdanchev/jupyter_for_reproducible_research
Jupyter for Reproducible Research
valdanchev/netrics_py27
Python 2.7.12 package for the econometric analysis of network data
valdanchev/Network-Science-with-Python-and-NetworkX-Quick-Start-Guide
Network Science with Python and NetworkX Quick Start Guide, published by Packt
valdanchev/Open-Collaborations
Open Collaborations is a Mozilla Open Leaders Project
valdanchev/Open-Data-Clinical-Trials
valdanchev/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
valdanchev/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
valdanchev/scipy-2019-pandas
Pandas tutorial for SciPy 2019
valdanchev/sklearn_tutorial
Materials for my scikit-learn tutorial
valdanchev/statistical-analysis-python-tutorial
Statistical Data Analysis in Python
valdanchev/ten-rules-jupyter
Ten Simple Rules for Writing and Sharing Computational Analyses in Jupyter Notebooks