Amazon Forecast vs. Jupyter Notebook

I personally get the feeling that Amazon Forecast must have been a direct product released on the models Amazon themselves must have used at some port. Amazon Forecast definitely shines when using it for product demand, inventory, and pricing throughout store locations, etc. Everything, including data-set importing, works best in this context. When applying it to more edge cases like resource planning around events, it can be a bit more tricky to apply effectively.

Incentivized

I would rate it 9/10 while recommending Jupyter Notebook as it offers me a wide range of functionality to operate. It is very well suited for someone who is new to python programming as the user interface helps you build code line by line. I personally have written multiple programs in Python using Jupyter Notebook as it helps me organize long code by breaking it in a structure. Also the ability to write comments using '#' helps a lot to a reader understand the code.

Incentivized

• Develop benchmarks for use in future forecast.
• Performs contingency planning during challenging financial times.
• Anticipate the impact of new expanse.

Incentivized

• Coding and error correction line by line
• Simple and Effectiveness
• Easy to use for visualisation and presentation of code
• Could be used at any place any time without hassle

Incentivized

• Potential very high costs
• Predicting ongoing running costs
• Very product focused

Incentivized

• Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
• Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.

Incentivized

Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.

Incentivized

I haven't had a need to contact support. However, all required help is out there in public forums.

Incentivized

There was no other product or service that was considered before making the choice to go with Amazon Forecast as the forecasting that the company was looking for had everything running in the AWS environment, the choice had to be obvious. Integrating with Amazon Forecast also ensured that everything is under a single roof and we didn't have to go multiple places looking for data when needed.

Incentivized

Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot of needs I have for EDA, modeling, and data export that makes other software products fairly redundant.

Incentivized

• Insights have been available much more quickly and well designed manner
• Integration with other tools has been flawless

Incentivized

• Positive impact: flexible implementation on any OS, for many common software languages
• Positive impact: straightforward duplication for adaptation of workflows for other projects
• Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration

Incentivized