sl7rf Goto Github PK
Name: Sasa Li
Type: User
Name: Sasa Li
Type: User
Notes and links from the book club meetings
Chinese poetry generation and deploy on Lambda/API Gateway
all config about bash/vim/alias etc.
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Auxilary scripts to work with (YOLO) darknet deep learning famework. AKA -> How to generate YOLO anchors?
Package to maintain a data cache.
Deep Learning Specialization by Andrew Ng on Coursera.
TensorFlow examples
Containing codes of participation in Kaggle competitions.
Winning solution for the National Data Science Bowl competition on Kaggle (plankton classification)
My code for Telstra Network Disruptions Kaggle competition
Code repository for Large Scale Machine Learning with Python, published by Packt
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.
This repository contains my ML scripts in R
Code of the IPython Minibook, 2nd edition (2015)
Machine Learning Operations (MLOps) are essential to build successful Data Science use-cases. Today, ML is powering data driven use-cases that are transforming industries around the world. In order to seize and hold it's competitive advantage business needs to reduce risk therefore a new expertise rises to include data science models in operational systems. According to Gartner Research βWhile many organizations have experimented with AI proofs of concept, there are still major blockers to operationalizing its development. IT leaders must strive to move beyond the POC to ensure that more projects get to production and that they do so at scale to deliver business value. (July 2020)β. In this session, we will discuss the role of MLOps and how they can help data science models from deployment to maintenance with focus on: keep track of performance degradation overtime from model predictions quality, setting up continuous evaluation metrics and tuning the model performance in both training and serving pipelines that are deployed in production.
Machine learning pipelines for R.
This is the tensorflow implementation of "Product-based Neural Networks for User Response Prediction".
Kriging Toolkit for Python
Welcome to the User Friendly Python Kriging Toolbox!
A growing collection of bare-bones GUI examples for python (PyQt4, Python 3)
A python implementation of the Rapid Automatic Keyword Extraction
Tutorial Sessions for SciPy Con 2019
SDS 385: Statistical Models for Big Data
Solvers for sigmoidal programming problems
A declarative, efficient, and flexible JavaScript library for building user interfaces.
π 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. πππ
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 β€οΈ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.