Machine Learning Programming with Tensorflow 2.0
Nikita Silaparasetty · Apress eBooks · 2020
So far, we have learned about artificial intelligence, under which we have machine learning and its sub-set, deep learning. We have also learned about the Python programming language, which is popularly used for machine learning coding. We even got familiar with the Jupyter Notebook interface, in which we can write, edit, and debug our programs. We then saw how we can combine Python with Jupyter Notebook as an efficacious way to write our code. After this, we were introduced to the TensorFlow library as an important package within Python, and once we understood how the library was useful, we proceeded to learn about its recent upgrade—TensorFlow 2.0—which has additional features and abilities that make our machine learning models easier to build.