Mike 's Projects
Productivity Tools for Plotly + Pandas
cuGraph - RAPIDS Graph Analytics Library
cuML - RAPIDS Machine Learning Library
Intro to K-Means clustering with cuML.
NumPy-like API accelerated with CUDA
Use CuPy ndarray with cuDF/cuML functions
Cornell CUSD Currents Team iOS app
GPU accelerated cross filtering with cuDF.
demo express.js app that uses d3.js to render svg charts server-side
iOS SwfitUI Tutorial
The Triton backend that allows running GPU-accelerated data pre-processing pipelines implemented in DALI's python API.
Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
Dash Analytics app
Apps hosted in the Dash Gallery
Parallel computing with task scheduling
Dask cuML provides a set of multi-GPU machine learning algorithms from cuML that integrate into the Dask ecosystem.
Docker images for dask
Scalable Machine Learn with Dask
Dask tutorial
Documenting how to use Dask-cuDF + Dask-XGBoost for training and prediction
General Assembly's Data Science course in Washington, DC
Data analytics using PowerBI for the Silicon Valley Diversity dataset
Swift Data-Driven UI examples
Exploratory data analysis, Scikit-learn, Jupyter, TensorFlow, PySpark, AWS
A Pythonic introduction to methods for scaling your data science and machine learning work to larger datasets and larger models, using the tools and APIs you know and love from the PyData stack (such as numpy, pandas, and scikit-learn).
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.
Automate Data Exploration and Treatment