Author List (in no particular order): Elias Castro Hernandez, Rajarathnam Balakrishnan, Ikhlaq Sidhu, Debbie Yuen, and Alexander Fred-Ojala
About (TL/DR): Tensorflow (TF) is an open-source library used for dataflow, differentiable programming, symbolic math ,and machine learning applications such as deep learning neural networks. TF's flexible architecture allows for easy deployment across varied processing platforms.
Learning Goal(s): This notebook covers advanced topics in machine learning. However, it does not require any prior knowledge in machine learning. The goal of this notebook is to teach a user how to deploy a TF model, as well as to provide the user guidance on how to tackle the more nuanced topics.
Associated Materials: To ease the learning curve, we encourage the user of this notebook to view the resources section on the main JupyterLab, and/or review the Data-X Fundamentals repo.
Keywords (Tags): tensorflow, tensor-flow, tensorflow-tutorial, deep-learning, deep-learning-with-python, neural-networks, data-x, uc-berkeley-engineering
Prerequisite Knowledge: (1) Python, (2) NumPy, (3) Pandas, (4) Linear Algebra
Target User: Data scientists, applied machine learning engineers, and developers
Copyright: Content curation has been used to expedite the creation of the following learning materials. Credit and copyright belong to the content creators used in facilitating this content. Please support the creators of the resources used by frequenting their sites, and social media.
- m410_shallow_neural_networks_introduction_to_tensorflow -- Overview of TensorFlow syntax, operations, and execution.
- assets/homeworks/ -- Contains several exercises to help you master the material.
1) PART 1.1: TENSORFLOW SETUP
2) PART 1.2: TENSORBOARD SETUP
3) PART 1.3: TENSORFLOW TENSORS
4) PART 1.4: TENSORFLOW OPERATIONS
1) PART 2.1: TENSORFLOW COMPUTATION FUNCTION -- \@tf.function
You've completed the introduction to TensorFlow V.2, and one can assume that you are ready to get things done with your new knowledge. Visit the Data-X website to learn how to use Tensorflow to tackle various deep learning problems, or use the following links to some topics of interest:
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