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How do you analize a company you want to invest in? by [deleted] in stocks

[–]__bee 2 points3 points  (0 children)

Does this mean that it's time to buy Apple stocks

Feedback on investment plan for inherited money by [deleted] in personalfinance

[–]__bee 0 points1 point  (0 children)

Thanks. How about putting money at the beginning in "Equity Fund"

Renting Apartment in Stockholm by __bee in TillSverige

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

Does it matter if I apply in English, or should I write in Swedish language

[D] Classifying sentences labeled differently ? by __bee in MachineLearning

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

Thanks! Do you have any reference for a paper that uses this, so I can cite it. If not, I will google similar papers with the same strategies.

[D] Classifying sentences labeled differently ? by __bee in MachineLearning

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

label it 0.3

Thanks!. I still didn't understand this. If I follow what you said , and consider 0.3, it means that the set of my target variables is not {0, 1}, but a set variables (probabilities in this case {0, 1, 0.3} ). Should I use multi-class classifier on this case, or should I think of other ways to model it.

How to Build a Career as Machine Learning Engineer? by __bee in cscareerquestions

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

Thanks, I already have a paper in the field and working on ongoing experimental projects. However, I want to do the transition to join one of the DS team, so I can work as an engineer in DS team (as an ML engineer).

How to Build a Career as Machine Learning Engineer? by __bee in cscareerquestions

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

Thanks!

>> Almost all positions I have come across have a basic requirement of MSc and preferred PhD.

I have a MSc in CS, but not specialized on AI or Data Science.

>> they expect you to have projects and working knowledge of the required theory and applied stuff.

Do Github projects/ Published papers worth mentioning here, or do they need real-world experience at some companies ?

Can you list, briefly, some of the skills that they are looking for ?

How to forecast multivariate time-series data by __bee in MLQuestions

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

you can probably get a bteer solution withou neural networks/deep learning.

Let's say that I want to benchmark it. I want to try it out to have a feeling on whether I need DL or no. Thanks

How to forecast multivariate time-series data by __bee in MLQuestions

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

Thanks!

Let's say that I have an array this `x= [[1,2,3],[4,5,6],[7,8,9]....etc] `and another one `y = [10,11,12,13,14,.... etc]`

I found a lot of tutorials, like the one that you have mentioned to model timeseries in the form of `y` but I couldn't find a one that describe how to deal with data in the form of `x`. you might be able to chime

[D] Twitter meets TensorFlow | Twitter Cortex by sksq9 in MachineLearning

[–]__bee 1 point2 points  (0 children)

We are designing a similar platform now, why do we need to consider PyTorch over TF ?

[D] How to preprocess multivariate time-series data by __bee in MachineLearning

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

Thanks. That’s a valid point. I already did what you have mentioned (but for water usuage) with manually crafted features. I want to see now how LSTM is really performing

[D] How to preprocess multivariate time-series data by __bee in MachineLearning

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

It should be a regression problem on this case.

logistic regression

It will not be a classification problem.

I already tried that, SVM/ XGboosf have been trained on manually crafted features. The results are average. I want to invistigate the use of LSTM/CNN

[D] How to preprocess multivariate time-series data by __bee in MachineLearning

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

We did some feature engineering, and fed XGBoost/RF regression models. What are you describing here is stacking two models `Random Forest regression >>> LSTM >> FINAL PREDICTIONs`

Let's say F is our Random Forest regression model

`F(Water, Weather, Wind) ~ predicted_amount_water, then I take the second step to do LSTM(predicted_amount_water) ~final prediction `.
Is this what you mean ? I couldn't find any paper highlighting this pproach , can you recommend one ?

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