Long Short-Term Memory Model

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Product Information

Type of Project
Subject of Project
Project Details
Material

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Maximium file size 100 MB

Project Packages

Packages 100$ Basic 140$ Standard 200$ Premium
Software Python-Jupiter notebook Python-Jupiter notebook Python-Jupiter notebook
Questions Writing 5 Queations* 10 Queations* 15 Queations*
Number of words 2000 Words** 5000 Words** 8000 Words**
Number of Pages 6 Pages 15 Pages 24 Pages
Topic Research
Plagiarism Check
Visualize Result
Source Code
Build a Documented Baseline Model
Add Second Model
Name Model
Add Third Model
Name Model
Dashboard
Revision Unlimited Unlimited Unlimited
Delivery time 3 Days*** 5 Days*** 7 Days***
Continue ( 100 $ )
Continue ( 140 $ )
Continue ( 200 $ )
$100
  • Python Jupiter Notebook
  • 5 Questions* Written
  • 6 Pages with 2000 words**
  • Free Source Code
  • Visualised Results
  • Unlimited Revisions
  • Delivered in 3 Days***
  • Add Second Model
  • Add Third Model
  • Select Dashboard
BASIC (100$)
$140
  • Python Jupiter Notebook
  • 10 Questions* Written
  • 15 Pages with 5000 words**
  • Get Researched Topic
  • Plagiarism Check
  • Free Source Code
  • Visualized Result
  • Unlimited Revisions
  • Delivered in 5 Days***
  • Add Second Model
  • Add Third Model
  • Select Dashboard
STANDARD (140$)
$200
  • Python Jupiter Notebook
  • 15 Questions* Written
  • 24 Pages with 8000 words**
  • Get Researched Topic
  • Plagiarism Check
  • Free Source Code
  • Visualised Results
  • Unlimited Revisions
  • Delivered in 7 Days***
  • Add Second Model
  • Add Third Model
  • Select Dashboard
PREMIUM ( 200$ )
  • The number of questions that are asked in the analysis of your contents Research /Report.
  • Approximately 250-333 words = one page.
  • xclude weekend days.

FAQs

How do you handle Models not working on python environment of the project?

When encountering a situation where a Python project is not working properly, utilize Excel or other software, seek expert advice if needed.

What types of tools in prediction can you measurement the error?

Common tools for measuring prediction errors include Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), R-squared (R²), and Mean Absolute Percentage Error (MAPE).

What level of detail do you provide in your reports?

We provide comprehensive reports that include key insights, conclusions, and recommendations. The level of detail will depend on your requirements and the complexity of the analysis.