fmfn / data-science-ipython-notebooksLinks
Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. https://bit.ly/data-notes
☆12Updated 9 years ago
Alternatives and similar repositories for data-science-ipython-notebooks
Users that are interested in data-science-ipython-notebooks are comparing it to the libraries listed below
Sorting:
- Tutorial on interpreting and understanding machine learning models☆69Updated 7 years ago
- A library of scalable Bayesian generalised linear models with fancy features☆60Updated 8 years ago
- python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.☆125Updated 5 years ago
- Course of Machine Learning in Science and Industry at Heidelberg university☆47Updated 8 years ago
- Repo for the ML_Insights python package☆153Updated 7 months ago
- Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference☆26Updated 6 years ago
- Slides and materials for most of my talks by year☆92Updated 2 years ago
- Experimental Gradient Boosting Machines in Python with numba.☆188Updated 6 years ago
- A helper library for data science pipeline☆36Updated 6 years ago
- Scikit-learn compatible implementations of the Random Rotation Ensemble idea of (Blaser & Fryzlewicz, 2016)☆43Updated 9 years ago
- PyMC3 tutorial for DataScience LA (January 2017)☆67Updated 7 years ago
- Scikit-learn API toy wrapper for Regularized Greedy Forests☆44Updated 9 years ago
- Experiments in Bayesian Machine Learning☆69Updated 6 years ago
- bayesian bootstrapping in python☆123Updated 3 years ago
- Ordinal Regression tutorial for the International Summer School on Deep Learning 2019☆70Updated 6 years ago
- A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.☆125Updated 5 months ago
- Analysis of Categorical Encodings for dense Decision Trees☆41Updated 8 years ago
- Machine Learning encoders for feature transformation & engineering: target encoder, weight of evidence, label encoder.☆23Updated 5 years ago
- a feature engineering wrapper for sklearn☆52Updated 5 years ago
- ☆25Updated 9 years ago
- Notebook demonstrating use of LIME to interpret a model of long-term relationship success☆24Updated 8 years ago
- 3-day dive into deep learning at csc☆25Updated 8 years ago
- PyData San Luis 2017 Tutorial: An Introduction to Gaussian Processes in PyMC3☆15Updated 8 years ago
- ☆159Updated 3 years ago
- Particle Gibbs for Bayesian Additive Regression Trees☆33Updated 10 years ago
- demos for PyBay talk: Using Randomness to make code faster☆51Updated 8 years ago
- Course in Probabilistic Programming in Python for the 2018 EU Summer School☆23Updated 7 years ago
- Creating a better validation set when test examples differ from training examples☆101Updated 9 years ago
- Some experiments into explaining complex black box ensemble predictions.☆74Updated 5 years ago
- Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.☆105Updated 6 years ago