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How to train a logistic regression model

Ok, I'm turning to the expertise on this forum to sanity check what I believe I've chanced upon. To put us on the same page the goal for a logistic regression is to determine a vector of real numbers which will serve as coefficients producing a linear combination of the feature vector values (plus a constant).  That said, I'm now going to present...

Anyone knows how to integrate data science with material science?

Hey guys,I have a masters in materials science and engineering and recently found an interest in data science. Could anyone guide me on how I can use my masters degree to have a career in data science. Thank you

How to change the email?

I changed my email. I received the verified email in my new email address. But when I key in the password, It showed no account with the new email.

Help others to get started with Machine Learning.

To democratize the organizational use of AI especially for those with little data, I have set up a survey to gain insights on the training of Machine Learning models on external data. https://www.surveyhero.com/s/external_data_sources_ML But I need your help (if you are training Machine Learning models on external data for organizational use). The...

How can I create an ensemble model which combines Market Mix Models and Multi touch attribution models?

I have been working on developing a unified marketing measurement model which combines the output of Market Mix Models and Multi touch attribution models. I came across articles where Bayesian priors is a suggested method, but I am yet to come across any research paper which actually discusses the details of implementation/feasibility of using this...

What to use data versioning for staging environment?

We are developing our end to end pipeline and realized data versioning for sampled data in dev environment using dvc works good, but what to use for staging env or production env. so that we can reproduce our older model.

Time Series - Stock Prediction Many Stocks

Usually I see example where we  have taken the data for a particular stock say 'GE' one company and predicting the prices for GE. Now if i have data for let say for 20 companies for the time period. So what should be the approach. My model should have the capability to predict stock prices for any of the 20 companies.

Opinions on PyCaret

Hello fellow Data Scientist ! I don't know if it's the right place to ask that but I guess so let's go. I just discovered Pycaret with this notebook : https://www.kaggle.com/servietsky/house-price-easy-modeling-easy-blending-ipynb/comments And it's seems to good to be real, it made a lot with so little. So Im' quite suspicious, what do you guys...

Analytics Best Practices Book

Last month I published my 2nd book - Analytics Best Practices. Here is the link to my book if DSC members are interested. This book provides ten key analytics best practices that will improve the odds of delivering enterprise data analytics solutions successfully. It is intended for anyone who has a stake and interest in deriving insights from data...

FFT on Time Series Data

Hi All: Quick question on Time series data and Fourier Analysis. Once you get the number of the Components (say 6 from FFT), how can one find the strength of each component in the time series data set or the normalized data? How can one decompose the time series data set based on the number of Components (say 6) proportionately? Rgds P

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