GA technologies Co., Ltd.

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Announcement of online study session on "Building a real estate rent forecast model"

October 18, 2024

We would like to inform you that we will be holding an online study session on "Building a Predictive Model for Real Estate Rent" on October 30th.

The workshop is a hands-on online workshop for participants of the "1st Ministry of Land, Infrastructure, Transport and Tourism Geospatial Information Data Challenge - Land and Numerical Information Edition", a cross-industry data competition using digital land information, held by the General Incorporated Association Real Estate and Construction Data Utilization Promotion Association (PCDUA) and the Ministry of Land, Infrastructure, Transport and Tourism. The workshop was taught by Takehiko Hashimoto of our Advanced Innovation Strategy Center (AISC), who used digital land information and data from private companies to build a real estate rent prediction model. We recommend that participants register for the competition in advance and prepare their work environment.

Product Management Product Manager / Advanced Innovation Strategy Center General Manager

Takehiko Hashimoto

After working at Sier (engineer for 5 years, researcher for 2 years) and a marketing research company (3 years), he joined BrainPad Inc. in 2008 as a senior data scientist, where he was mainly involved in data analysis in the marketing field and launching new businesses to train data scientists. He participated in the launch of the The Japan DataScientist Society, and was appointed Secretary General of the organization in 2015 (-2018). He also focuses on industry-academia collaboration and human resource development activities, such as giving lectures at multiple universities, including Shiga University, Keio SFC, and Waseda University. In April 2017, he joined GA technologies and participated in the launch of the Advanced Innovation Strategy Center (formerly the AI Strategy Office). He is responsible for the Group's data management and external affairs. From April 2019, he has been a visiting associate professor at the University of Electro-Communications, National University Corporation, Industrial Academic-Government Collaboration Center. From April 2021, he has been an industrial advisor at the Faculty of Data Science, Shiga University, National University Corporation. Member of the Ministry of Land, Infrastructure, Transport and Tourism's Real Estate ID Rule Review Committee from April 2020 to March 2021. Publications: "Data Science Exercises for Working Adults" (Statistics Bureau, Ministry of Internal Affairs and Communications), "Statistics Guidance" (Nihon Hyoronsha/co-author), and others.

[Study session overview]
Theme: Building a real estate rent prediction model using provided digital land information and private company data
Date and time: Wednesday, October 30, 2024 19:00-21:00
Location: Zoom online
Participation fee: Free
Eligible participants: SIGNATE members who wish to participate in the competition (beginners in Python and SQL)
Organized by: Ministry of Land, Infrastructure, Transport and Tourism
Planning and management: Real Estate and Construction Data Utilization Association (PCDUA)
Sponsored by: GA technologies

■Lecture environment *Online lectures
・Google Colab (analysis)
・SIGNATE (Competition Platform)
・Zoom Webinars (online lectures (distribution))
・Slack (for questions, etc.)

■ Usage data
・National Land Numerical Information (provided by the Ministry of Land, Infrastructure, Transport and Tourism) - GIS data including geospatial information for the entire country "National Land Numerical Information"
・Registry office map data (provided by the Ministry of Justice) - Electronic data of maps and drawings related to real estate registration "Registry office map"
・Property data (provided by LIFULL Co., Ltd.) - Rent and property information for rental apartments and condominiums nationwide from 2019 to 2023
・ZENRIN Maps API (provided by Zenrin Co., Ltd.) - API with functions that can be used for preprocessing and feature creation, such as address cleansing and map drawing

■Environment
・Land Bank (provided by Netdata Co., Ltd.)
・Databricks analysis environment (provided by Databricks Japan Co., Ltd. and Microsoft Japan Co., Ltd.)
・Snowflake analysis environment (provided by Snowflake LLC)

■Curriculum for the day
1. Competition overview and data explanation
2. Explanation of the data analysis process
3. (Introduction) Let's try predicting rents simply!
4. (Advanced Part 1) Let's visualize it on a map and think about it!
5. (Advanced Part 2) Use APIs to incorporate various data!

Register for the online workshop here

More details about the competition here

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