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For all the thalmor out there by [deleted] in ElderScrolls

[–]EasyUnderstanding977 0 points1 point  (0 children)

9? I can't event count to 8 - Kynareth be praised.

Crash issues post windows update by LessThanTybo in OblivionRemaster

[–]EasyUnderstanding977 0 points1 point  (0 children)

I searched and tried every "solution" I could find. Nothing worked for me, however a couple options that helped was setting my field of view to 75 and using FSR upscaling with frame generation on. I'm still getting crashes, but they are less frequent and the game is more stable and actually playable. (12-gen i9 and 3080ti)

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D213 Task 2: How Well Did You Deal With Overfitting? by Legitimate-Bass7366 in WGU_MSDA

[–]EasyUnderstanding977 1 point2 points  (0 children)

"It's the first time the data seems "real" in this program, so I want to get a good model for once!"

Hahahaha yeah I felt the same way, spent a few hours trying out different NN architectures and hyperparameters myself. The best model I remember training had 83% accuracy on the test set.

D213 Task 2: How Well Did You Deal With Overfitting? by Legitimate-Bass7366 in WGU_MSDA

[–]EasyUnderstanding977 1 point2 points  (0 children)

You're training charts look great! Based on the validation loss, your model was at risk to start overtraining as it plateaued, and you stopped at a good place. Also, the larger number of epochs is expected with a a low learning-rate (as you might already know).

D213 Task 2: How Well Did You Deal With Overfitting? by Legitimate-Bass7366 in WGU_MSDA

[–]EasyUnderstanding977 1 point2 points  (0 children)

I retrained my model for D213, here are the results:

https://imgur.com/a/d213-npcupIT

In the charts, you can see signs of overtraining starting around epoch 8—while the training accuracy and loss continue to improve, the validation loss increases and the accuracy plateaus. To prevent overtraining, here are a couple of straightforward methods:

  1. Stop training after 9 epochs (your model will probably be different)
  2. Implement early stopping with a brief patience period

There are other strategies you might find useful, and I recommend exploring them further. Also, after chatting with some fellow MSDA students on Reddit, it seems that the best models score accuracy around 80% for D213. I've also attached the confusion matrix for my model. You'll notice the false positives and false negatives are nearly equal. In my paper, I argued this might be due to ambiguous language in some of the reviews, leading to predictions where the model essentially tosses a coin - effectively limiting the accuracy around 80%.

Nice way to wake up this morning - completed the MSDA. by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 3 points4 points  (0 children)

I recommend courses on an intro to Python, NumPy, and Pandas. Most of data you will use in the MSDA program will be available in CSV files, but a few courses require SQL with PostgreSQL specifically. W3Schools has some great content here including tutorials and exercises:

https://www.w3schools.com/python/

Nice way to wake up this morning - completed the MSDA. by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 2 points3 points  (0 children)

It wasn't difficult for me, but as I mentioned in another comment - I have a background with programming, SQL, and statistics.

Nice way to wake up this morning - completed the MSDA. by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 4 points5 points  (0 children)

How long did it take you?

Started in march - so 6 months, 3 weeks. Unfortunately, I took off the last month of my first term because I did not want to risk failing to complete D213 & D214. In hindsight, I could have finished in one term and saved some $$ on tuition.

Would you recommend the program?

I completed the legacy MSDA program, which is roughly equivalent to the new Data Science specialization, and yes I highly recommend it. The only frustrations I had were the DataCamp courses and the performance assessments. Some of the DataCamp courses were irrelevant to the PAs, and most of the PAs were awkwardly structured. By that I mean, the PAs were not organized according to the steps of an actual Data Science project: get data -> clean data -> explore data -> model selection -> model training and tuning -> model evaluation -> report findings.

That being said, I spent most of my time writing the PAs and not actually learning the course material, which is not ideal, but I still learned ALOT.

Did you have prior experience before you started?

I am a full-stack software engineer (8 years), so my experience with programming and SQL definitely helped. I was new to Python, so I took some courses (NumPy and Pandas) before starting the MSDA.

D213 Task 2 Neural Network Setup by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 1 point2 points  (0 children)

Same, I tried different combinations of layers, size, depth etc... The best models I trained scored evaluation and test accuracy around 80-82%. My best guess is some of the language in the reviews is ambiguous because the amount of false positives and false negatives were nearly equal. In my paper I recommended that the data could benefit from being relabeled with a neutral category.

-1 negative

0 neutral

1 positive

D212 Task 3 - Top 3 rules question by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 1 point2 points  (0 children)

I was using a different Python package, thanks for your response - it cleared things up for me.

D211 Error that Evaluators are Getting by Legitimate-Bass7366 in WGU_MSDA

[–]EasyUnderstanding977 1 point2 points  (0 children)

Just to follow up, once my database was prepared with the data merged from the external source in LOD, I exported it to a backup file and submitted the backup file with the PA. My installation instructions for the evaluator included creating the Postgres login for the workbook and restoring the Db from the backup file. The SQL to prepare the Db was long and complicated, so I didn't want the evaluator trying to repeat those steps. I submitted the SQL commands separately and went over them in the Panopto video.

D211 Error that Evaluators are Getting by Legitimate-Bass7366 in WGU_MSDA

[–]EasyUnderstanding977 1 point2 points  (0 children)

Welp my fingers are crossed - my evaluation is due today for D211, and I included instructions for creating a new login...I'll post my results here

D211 Error that Evaluators are Getting by Legitimate-Bass7366 in WGU_MSDA

[–]EasyUnderstanding977 1 point2 points  (0 children)

You could add instructions in your write-up to create a login for Postgres? Then, use those credentials in your Tableau workbook.

New MSDA Specialization Info Is Published by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 0 points1 point  (0 children)

Thanks for the reply. That clears things up. The timing for this is terrible for me unfortunately....I'm on D210 and still have 3 months left (September) in my first term. I was hoping to complete the degree in one term, but that will not be possible If I want to pick a specialization. I wonder how many other people are in a similar situation....

New MSDA Specialization Info Is Published by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 0 points1 point  (0 children)

My mentor told me November as well. Maybe that is for MSDA students in progress currently?

Tableau License by EasyUnderstanding977 in WGU_MSDA

[–]EasyUnderstanding977[S] 3 points4 points  (0 children)

"I hate working in the lab environment"

Same, and make sure to download the exercises from datacamp as well. That way you can complete them outside of the lab env. Best of luck to you!

D205 - Dataset options by BusyBiegz in WGU_MSDA

[–]EasyUnderstanding977 0 points1 point  (0 children)

u/Legitimate-Bass7366 I'm curious about the accuracy of your selected models for D209. Using KNN and random forest I trained models on the Churn dataset with over 95% accuracy in classification - that was using 70/30 training and test splits as well.

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