Discover @ivanliu1989 Open Source projects

Tianxiang(Ivan) Liu (@ivanliu1989)

ivanliu1989

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Registered almost 10 years ago
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R
50.0 %

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HTML
8.3 %

C++
4.2 %

Objective-C
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Location 🇨🇳 China
Country Total Rank 19,205
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R
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Jupyter Notebook
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Objective-C
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Python
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AVAZU-CTR-Prediction

In online advertising, click-through rate (CTR) is a very important metric for evaluating ad performance. As a result, click prediction systems are essential and widely used for sponsored search and real-time bidding.

Predict-click-through-rates-on-display-ads

Display advertising is a billion dollar effort and one of the central uses of machine learning on the Internet. However, its data and methods are usually kept under lock and key. In this research competition, CriteoLabs is sharing a week’s worth of data for you to develop models predicting ad click-through rate (CTR). Given a user and the page he is visiting, what is the probability that he will click on a given ad? The goal of this challenge is to benchmark the most accurate ML algorithms for CTR estimation. All winning models will be released under an open source license. As a participant, you are given a chance to access the traffic logs from Criteo that include various undisclosed features along with the click labels.

Real-time-Mobile-Video-Object-Detection

Jupyter Notebook

SwiftKey-Natural-language

SwiftKey, our corporate partner in this capstone, builds a smart keyboard that makes it easier for people to type on their mobile devices. One cornerstone of their smart keyboard is predictive text models.

Mapbox-Navigation-React-Native

KDD2015

Afr-Soil-Prediction

Advances in rapid, low cost analysis of soil samples using infrared spectroscopy, georeferencing of soil samples, and greater availability of earth remote sensing data provide new opportunities for predicting soil functional properties at unsampled locations. Soil functional properties are those properties related to a soil’s capacity to support essential ecosystem services such as primary productivity, nutrient and water retention, and resistance to soil erosion. Digital mapping of soil functional properties, especially in data sparse regions such as Africa, is important for planning sustainable agricultural intensification and natural resources management.

Melbourne_Datathon_2016_Kaggle

The objective is to predict if a job is in the 'Hotel and Tourism' category.

edxIntroSpark

Introduction to Big Data with Apache Spark on edx

Human-Activity-Recognition

Human Activity Recognition - HAR - has emerged as a key research area in the last years and is gaining increasing attention by the pervasive computing research community Read more: http://groupware.les.inf.puc-rio.br/har#ixzz3DWwgwZM1, especially for the development of context-aware systems. There are many potential applications for HAR, like: elderly monitoring, life log systems for monitoring energy expenditure and for supporting weight-loss programs, and digital assistants for weight lifting exercises.

bike-sharing-data-mining

Bike sharing systems are a means of renting bicycles where the process of obtaining membership, rental, and bike return is automated via a network of kiosk locations throughout a city.

Data-Science-Practical-Machine-Learning

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation.

RQuantFX

RQuantTrader

PyQuantTrader

Algo trading backtesting & live AB testing framework

Jupyter Notebook

Melbourne_Datathon

AutoPairTrading

RQuantAPI

Tradeshift-Text-Classification

In this competition, participants are asked to create and open source an algorithm that correctly predicts the probability that a piece of text belongs to a given class.

two-sigma-financial-news

Use news analytics to predict stock price performance $100,000

Jupyter Notebook

EventDrivenForexTrading

Fraud-detection-kumar

Detecting Fraudulent Transactions

Otto-Group-Product-Classification-Challenge

For this competition, we have provided a dataset with 93 features for more than 200,000 products. The objective is to build a predictive model which is able to distinguish between our main product categories. The winning models will be open sourced.

Helping-Santas-Helpers

Every year Santa has to satisfy a grueling toy-production schedule. Toy orders arrive all year long and the Elfin Workers Union is stronger than ever. Let's help Santa develop a job scheduling algorithm that meets his toy target while keeping his elves healthy and happy.