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Examples of Data Science projects and Artificial Intelligence use-cases

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artificial-intelligence classification computer-vision data-science data-visualization deep-learning examples explainable-ai explainable-ml machine-learning natural-language-processing python regression reinforcement-learning time-series

datascience_artificialintelligence_utils's Introduction

I code & write about coding, check out my stuff ๐Ÿ‡ฎ๐Ÿ‡น ๐Ÿ‘ฝ ๐Ÿ‘ป

mdipietro09

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๐Ÿ’ป Welcome to my office, here you shall find the following repositories/projects:


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datascience_artificialintelligence_utils's Issues

features_selection function is returning same features for different target classes

Hi I'm building a binary classifier model that uses text data as input, I tried to generate features using features_selection function, but it was returning the same number of features for the two different target classes which is actually incorrect. Am I supposed to generate the features separately for the two classes?

#Feature Selection
X_names, df_selection = features_selection(X_train, df_train["Target"], X_names, top=None, print_top=25)

Output:

features selection: from 10,000 to 7,026
 
# Curate:
  . selected features: 7026
  . top features: aa, acid, acid sequence, activity, advance, affinity, allergen, alpha, amino, amino acid, antibody, antigen, antigenic, antimicrobial, antimicrobial peptide, application, approach, area, article, aspect, assay, assessment, attention, autoantibody, autoimmune
 
# Discard:
  . selected features: 7026
  . top features: aa, acid, acid sequence, activity, advance, affinity, allergen, alpha, amino, amino acid, antibody, antigen, antigenic, antimicrobial, antimicrobial peptide, application, approach, area, article, aspect, assay, assessment, attention, autoantibody, autoimmune

df_selection[df_selection['feature'] == 'protein']
feature score y
protein 1.0 Curate
protein 1.0 Discard

requirements.txt conflict in NLP pip 21.2.4

The conflict is caused by:
The user requested numpy==1.16.4
pandas 0.25.1 depends on numpy>=1.13.3
matplotlib 3.1.2 depends on numpy>=1.11
seaborn 0.9.0 depends on numpy>=1.9.3
scikit-learn 0.22 depends on numpy>=1.11.0
lime 0.1.1.37 depends on numpy
tensorflow 2.6.0 depends on numpy~=1.19.2

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