Robert Schroll introduces TensorFlow's capabilities through its Python interface with a series of Jupyter notebooks, moving from building machine learning algorithms piece by piece to using the higher-level abstractions provided by TensorFlow. You'll then use this knowledge to build and visualize machine learning models on real-world data.
Practical machine learning with the Jupyter Notebook
Christian Moscardi (The Data Incubator)
Christian Moscardi walks you through developing a machine learning pipeline, from prototyping to production, with the Jupyter platform, exploring data cleaning, feature engineering, model building and evaluation, and deployment in an industry-focused setting. Along the way, you'll learn Jupyter best practices and the Jupyter settings and libraries that enable great visualizations.