Name: Mike
Type: User
Company: dataconsulting
Bio: Freelance Startup Consulting
Location: nyc
I am consultant in data science, machine learning, artificial intelligence.
I am also looking for full-time employment. I tend to work on quite a few projects, as many as time permits, but my focus is mostly around the following areas:
You can check out my website: anhmike.github.io
cufflinks
Productivity Tools for Plotly + Pandas
cugraph
cuGraph - RAPIDS Graph Analytics Library
cuml
cuML - RAPIDS Machine Learning Library
cuml_kmeans
Intro to K-Means clustering with cuML.
cupy
NumPy-like API accelerated with CUDA
cupy-cudf-cuml
Use CuPy ndarray with cuDF/cuML functions
cupy-performance
currents-ios
Cornell CUSD Currents Team iOS app
cuxfilter
GPU accelerated cross filtering with cuDF.
d3-server-side-demo
demo express.js app that uses d3.js to render svg charts server-side
dadjokes-ios
iOS SwfitUI Tutorial
daily-stock-forecast
dali_backend
The Triton backend that allows running GPU-accelerated data pre-processing pipelines implemented in DALI's python API.
dash
Analytical Web Apps for Python, R, Julia, and Jupyter. No JavaScript Required.
dash-analytics-report
Dash Analytics app
dash-sample-apps
Apps hosted in the Dash Gallery
dask
Parallel computing with task scheduling
dask-cuml
Dask cuML provides a set of multi-GPU machine learning algorithms from cuML that integrate into the Dask ecosystem.
dask-docker
Docker images for dask
dask-examples
dask-ml
Scalable Machine Learn with Dask
dask-tutorial
Dask tutorial
dask-xgboost-docs
Documenting how to use Dask-cuDF + Dask-XGBoost for training and prediction
dat8
General Assembly's Data Science course in Washington, DC
data-analytics-powerbi
Data analytics using PowerBI for the Silicon Valley Diversity dataset
data-driven-vc
Swift Data-Driven UI examples
data-science-and-machine-learning-bootcamp
Exploratory data analysis, Scikit-learn, Jupyter, TensorFlow, PySpark, AWS
data-science-at-scale
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-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.
dataexplorer
Automate Data Exploration and Treatment
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
Django
The Web framework for perfectionists with deadlines.
Laravel
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft
Open source projects and samples from Microsoft.
Google
Google ❤️ Open Source for everyone.
Alibaba
Alibaba Open Source for everyone
D3
Data-Driven Documents codes.
Tencent
China tencent open source team.
