TIANCHI Purchase Redemption Forecast Challenge

Last update: Aug 26, 2022

Overview

TIANCHI-Purchase-Redemption-Forecast-Challenge

My solution of this Aliyun Tianchi challenge (https://tianchi.aliyun.com/competition/entrance/231573/introduction).

Achieved online score: 132.89, Ranking TOP 5% (431/8452, updated on 2022.1.29)

Introduction：

The challenge focuses on forecasting the daily capital inflow and outflow of the “YuEBao” monetary fund in the future. For the monetary fund, capital inflow means purchase, and capital outflow is redemption.

Datasets and its description are available at the official website of this challenge

Repository Structure:

Notebook for exploratory data analysis
Notebook for feature engineering and modeling
A report(Chinese, English version might be available in the future) for impelemental details and analysis for this project

Note:

All codes are for reference only and shall not be used for commercial purposes without permission. If you have any questions about the code, please contact: [email protected]

Owner

Haorui HE

Software Engineering; Machine Learning; Deep Learning; NLP; Data Science

GitHub Repository

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TIANCHI Purchase Redemption Forecast Challenge

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Overview

TIANCHI-Purchase-Redemption-Forecast-Challenge

Introduction：

Repository Structure:

Note:

Owner

Haorui HE

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TIANCHI Purchase Redemption Forecast Challenge

Related tags

Overview

TIANCHI-Purchase-Redemption-Forecast-Challenge

Introduction：

Repository Structure:

Note:

Owner

Haorui HE

A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search (Manhattan Distance Heuristic)

CVXPY is a Python-embedded modeling language for convex optimization problems.

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Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

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PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors.

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