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Join me in this hands-on data science video as I walk through the solution to a forecasting competition. Learn how to approach data science projects and competitions with practical tips and techniques to succeed in the field.

📖CHAPTERS
00:00 Introduction
01:29 Competition Context
04:18 The Starter Notebook
34:06 Data Preparation
57:11 Isolated Series Approach
01:25:20 Analysis and Feature Engineering
02:02:34 Clustering Series Approach
02:18:37 My Final Solution
02:44:30 The Winner's Solution
02:56:45 Outro and Thanks!

🔗LINKS AND CHAPTER REFERENCES

My Video on The Competition Journey:    • Can I WIN a Data Science Competition?🏆  
My Solution Repo: https://github.com/trentpark8800/zind...

Competition Context:
Competition Link: https://zindi.africa/competitions/ibm...

The Starter Notebook:
ARIMA Explanation:    • ARIMA Model Explained | Time Series Foreca...  
Time Series vs ML:    • Why Are Time Series Special? : Time Series...  
Stationarity:    • Time Series Talk : Stationarity  

Data Preparation
DuckDB: https://duckdb.org/
DuckDB Tutorial: https://realpython.com/python-duckdb/

Isolated Series Approach
Darts Quikstart: https://unit8co.github.io/darts/quick...

Clustering Series Approach
My Video on KMeans Clustering:    • Hands On Data Science Project: Understand ...  
tsfresh: https://tsfresh.readthedocs.io/en/lat...

My Final Solution
My Video on Linear Regression:    • Linear Regression is More Important Than Y...  
My Video on Optuna:    • The Best Way to Tune Hyperparameters? | Gr...  

The Winner's Solution
Winner's Repo: https://github.com/bakarys01/hydropow...


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