Employee Training Tracker

I am using SharePoint 2013, I have the following 2 lists, noted below.

I need to copy the names of the 10 courses in the Course List over to the Main List and associate a new user’s profile name (Person or Group) to each of the 10 courses. Once notified the user will complete the required course, upload their certificates and enter the Start and Expiry date in the Main List.

I will need to repeat the same process for each additional new user. I’ll be also using the list to track the individual/overall status of who has/has not completed the required courses.

  1. Main List: (contains the record of all users and the courses they’ve completed)

    • Profile Name: Person or Group
    • Course Name: Lookup (Course List)
    • Start date: Date and Time
    • Expiry Date: Date and Time
    • Attachments: Users upload their course certificate
  2. Course List: (contains the name of the courses ( currently 10 courses) that the users must complete)

    • Course Name: Single line of text
    • Description: Single line of text
    • Frequency: Choice

Any help will be greatly appreciated.

System shuts down when training ml models

I have a system with 4xRTX2080 used primarily for ml model training.

Nvidia driver version: 430.26 CUDA Version: 10.2 

I use VSCode’s remote development extension to remote into the machine and start the training. The GPU usage is usually higher than 70% on all 4 GPUs when training.

If I leave the system like this for ~12 hours the ssh connection will break, the computer will go offline, but the pc won’t power off. If I hook up a keyboard and a monitor to it, there is no output signal to the monitor, and the pc doesn’t react to the keyboard input.

It’s very important for me to be able to leave the training for longer periods of time without worrying that the computer will turn off.

How do I even begin to debug this?

Why does a RNN network output different based on the training sequence

I’ve set up an RNN LSTM network in Java using DL4J as the library.

I currently have 500 examples of positive text, and 500 examples of negative text.

When I fitness the training data by first training all the negatives and then all the positives, my predictions only favor high positive responses even for things that would be considered negative in my training examples.

And if I reverse it and train positive first and then train negative last everything is favored as a negative in high 80 – 90%.

However, when I train in an oscillating pattern such as: Positive, Negative, Positive, Negative and so on, the predictions become accurate again and similar examples of negative text are picked up relatively accurately and vice versa for positive text.

I’ve only just started studying machine learning in general but I can’t quite find any resources explaining why the sequence of training impacted my model so hugely. Is this normally how an LSTM network should behave or is oscillating the training data the correct approach?

Would the classification of a messages negative intent be something an LSTM RNN network should be used for or should I consider another network?

SAS training y practica

Actualmente soy desarrollador python y me empresa necesitan que tambien aprendamos SAS.

Estan haciendo el proceso de selección un poco a la inversa bajo mi punto de vista. Quieren a un desarrollador que no tenga mucha idea de SAS pero que algo (ligeramente) si tenga para pasar una entrevista el proximo miércoles. Yo soy ese candidato al que han elegido para le entrevista, se poco o nada sobre SAS y me preguntaba si vosotros serias tan amables de decirme si existiese alguna maquina virtual o algo que me pueda servir para tener un ligero conocimiento técnico.

Muchas gracias a todos.

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How to fix my code from the tutorial, Training YOLOv3 : Deep Learning based Custom Object Detector?

So I have tried the tutorial Training YOLOv3 : Deep Learning based Custom Object Detector from learnopencv, but I cannot manage to correctly implement it. I have correctly followed all the steps from 1-6. But I have a problem at step 7. When I train the darknet model, I get the following reply Loading weights from ./darknet53.conv.74...Done!

But after that, nothing happens. I have let it run for an hour but I see no result, and there is no change to my train.log file. How should I fix this? Also, I am running this code on my Macbook terminal(would I need to use a VM instead?).

Thanks for your help, Hernades Freeman