Skip to content

pcavad/beginning-data-science

Repository files navigation

Collection of notebooks which I prepared along the specializations:

  • Data Science professional with IBM
  • Advanced Data Science with IBM
  • Machine Learning with IBM
  • AI Engineering with IBM

I also included a folder with links to visualizations (Google Data Studio and Tableau).

Content:

    1. Capstone project Adavanced Data Science with IBM specialization (image classification with a CNN).
    1. Capstone project Data Science with IBM specialization (unsupervised classification).
    1. Capstone project Machine Learning with IBM specialization (image classification with a CNN and optimizations).
    1. Capstone project AI Engineering with IBM (image classification with pre-trained ResNet50 and VGG16).
    1. Machine Learning projects (regression, classification, clustering).

Note: code style and conventions in the notebooks mirror a learning path.

Programming: python.

Tools: Jupyter Notekook (.ipynb)

Libraries:

  • pandas
  • numpy
  • matplotlib
  • seaborn
  • os
  • sklearn
  • statsmodels
  • scipy
  • keras
  • TensorFlow
  • PyTorch
  • folium
  • Foursquare API