Forecasting Rainfall – 8 week ML Solution with Omdena | Kanda Weather

This machine learning real-life case dealt with collaborating on a team of 50+ data scientist volunteer collaborators to build a 12-hour Rainfall Forecasting AI Model to Mitigate Climate Change Variability in West Africa.

The solution took place over a period of eight to ten weeks between Omdena collaborators and Kanda Weather Group to help build a 12-hour rainfall forecasting AI model to mitigate climate change variability in west Africa with a particular interest in Douala, Cameroon.

Omdena collaborators explored various ways of finding better insights to the datasets provided by Kanda Weather by data collectiondata cleaning, exploratory data analysis (EDA), model building, and deployment techniques.

My role within this high-impact challenge for Omdena was to Lead the Exploratory Data Analysis Task.

Exploratory Data Analysis Task Lead

I was responsible for leading collaborators through phase of exploratory data analysis (EDA).

This entailed:

  • attending regular meetings for other tasks such as data collection and data preparation/cleaning so as to be up to speed on the project progression and especially any down-stream effects for data analysis (as you may discover as you read the document attached).
  • leading the team through the EDA tasks by way of weekly task meetings as well as preparing and/or presenting at the weekly team meetings to the partner
  • preparing and presenting at the Mid-Term meeting to the partner on findings and result up to the point
  • collaboratively working with all task leaders to prepare the final report on the project to the partner, as well as preparing/finalizing and presenting at the Final Presentation to the partner.

Skills: Data Processing · Data Transformation · Data Manipulation · Analytics · Exploratory Data Analysis · Communication · Data Analysis · Analytical Skills · Microsoft Excel · Organization & prioritization skills · Knowledge Sharing · Data Visualization · Data Science · Machine Learning · Python (Programming Language) · Data Mining · GitHub · DagsHub · Collaborative Problem Solving · Teamwork

Certificate of Completion

Summary of Project – Document

The summary document provided here is a shorter version of the final document presented to the partner. Being a task lead, I was responsible for contributing to this document, especially in writing the EDA analysis and findings (which is provided in a second document below with further details).

EDA Analysis & Findings

Being a team lead for EDA a lot of the content written and presented in the EDA section was my own responsibility to the team. However, all of the team leads participated in writing the overall perspectives of the findings.

Additionally, there is a second of data analysis that was performed by me in order to present the distribution of seasonality over time, and how that impacted the data possibly.

Thank you for viewing this relevant pieces of work and contribution to this great and impactful ML Project

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