achillessaxby Goto Github PK
Name: Achilles Edwin Alfred Saxby
Type: User
Bio: Probable philosopher, weird thinker, educated statistician & a hopeful data scientist. Absolutely and unequivocally nuts.
Location: Brooklyn, New York, USA.
Name: Achilles Edwin Alfred Saxby
Type: User
Bio: Probable philosopher, weird thinker, educated statistician & a hopeful data scientist. Absolutely and unequivocally nuts.
Location: Brooklyn, New York, USA.
:computer: Data Structures and Algorithms in Python
The most cited deep learning papers
A curated list of awesome Machine Learning frameworks, libraries and software.
Predict delay for NYC bus network
fast.ai Courses
hackathon with pitches from CUSP Alumni working in NYC agencies
Introductory Material for Basic Data Analyses
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.
MinHash, LSH, LSH Forest, Weighted MinHash, b-bit MinHash, HyperLogLog, HyperLogLog++
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Deep learning tutorial for PyData London 2016
The fastai deep learning library, plus lessons and and tutorials
Solutions of challenges of Hackerrank Python domain
Repo for all analysis done for highilne
The Hitchhiker's Guide to Data Science for Social Good
Deep Learning for humans
Oxford Deep NLP 2017 course
Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
Content for Udacity's Machine Learning curriculum
Python code for common Machine Learning Algorithms
Machine Learning From Scratch. Bare bones Python implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from data mining to deep learning.
This repo contains all machine learning projects which I undertook.
Open Machine Learning Course
📙 Amazon Web Services — a practical guide
A machine-readable format for storing and sharing water rate structures.
Examples and guides for using the OpenAI API
Machine Learning Scripts on some datasets.
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 ;)
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 is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
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.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.