pcavad / beginning-data-science

Showcase edu

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).
• 2. Capstone project Data Science with IBM specialization (unsupervised classification).
• 3. Capstone project Machine Learning with IBM specialization (image classification with a CNN and optimizations).
• 4. Capstone project AI Engineering with IBM (image classification with pre-trained ResNet50 and VGG16).
• 5. 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