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Data Science

Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from structured and unstructured data. Data scientists perform data analysis and preparation, and their findings inform high-level decisions in many organizations.

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sh-biswas
sh-biswas commented Mar 9, 2021

It appears that the docs for Logistic Regression differ based on solvers and penalties. The "penalty" parameter states that "The ‘newton-cg’, ‘sag’ and ‘lbfgs’ solvers support only l2 penalties," while the "solver" parameter states that "‘newton-cg’, ‘lbfgs’, ‘sag’ and ‘saga’ handle L2 or no penalty" (attaching some screenshots). This was actually a little unclear to me, as I wasn't sure if the n

superset
john-bodley
john-bodley commented Apr 8, 2021

If a metric is removed from a datasource the single metric widget is inoperable if saved slice or URL references the previously defined metric. Note this isn't a problem for visualization types which support multiple metrics.

Expected results

The metric widget to render correctly.

Actual results

The metric widget in inoperable (see attached screenshot).

Screenshots

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Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  • Updated Feb 18, 2021
  • Python
dash
thiemoToadi
thiemoToadi commented Apr 6, 2021

Summary

When import streamlit and supervisely_lib together in a project there occurs a TypeError.

Steps to reproduce

Code snippet:

import streamlit as st
import supervisely_lib as sly

If applicable, please provide the steps we should take to reproduce the bug:

  1. run the code with streamlit run ...
  2. see error/traceback when you open the streamlit page
pytorch-lightning
gensim