P4: Predict Store Item demand prediction
Project Update:
After spending a considerable amount of time paper, pencils, and deriving mathematical equations for the previous project — Implementing Regression from scratch, I decided to take a break before proceeding to Advanced Regression algorithms from scratch.
For Project4 of 100MLProjects, I’ve opted to work on TimeSeries Forecasting. The fact that I do not know much about Time Series, is the main reason why I wanted to take up this project.
There is a live competition and a past contest in Kaggle. For learning purposes, I’ll work on the past contest for this project.
I’m going to be working on Store Demand Forecasting Challenge, and work on the datasets provided there.
I have gathered the following resources for now:
- AnalyticsVidhya: Comprehensive beginners guide to create time series forecasting.
- Towards DataScience: An End-to-End Project on Time Series Analysis and Forecasting with Python
- Kaggle: Time Series Prediction tutorial with EDA
- Kaggle: Time Series Analysis in Python
- YouTube Playlist: TimeSeries Modeling and Analysis
Note: Will start working on this from July 06, 2020.
So Far So Good:
Sharing my work & experiences, and reaching out to experts for help are really good strategies to build meaningful contacts within the domain. Many appreciated the initiative, and few extended their interest to join with me on this journey. Many shared suggestions and comments on future project ideas, where to look for resources, and lots more. I’m really grateful for all of your inputs.
For Project4(and most probably Project5), I’m going to work with Ram Vignesh. We both will work independently first, trying to build our own versions first, and then share our learnings with each other to improvise our end-result. We will share the minutes of our discussion in a future blog post, so it might help someone.
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You can reach out to me through LinkedIn or Email: WriteTo@Laxmena.com
