Introduction to TensorFlow Fundamentals

<p>This is the first lab in the Machine Learning with TensorFlow series. The primary focus of this lab is to help you understand the fundamental components of TensorFlow.</p> <h3>Learning Objectives:</h3> <div> <ul> <li>Creating scalars, vectors, matrices, and tensors</li> <li>Inspecting different attributes of a tensor.</li> <li>Performing basic operations on tensors.</li> <li>Learn to index and slice tensors.</li> <li>Reshaping and manipulating tensors.</li> </ul> <h3>To get the most out of this series:</h3> <ul> <li>you should know how to write code, ideally have some experience programming in Python.</li> <li>have a decent understanding of variables, linear equations, matrices, calculus, and statistics.</li> <li>don't just stick to the examples and code I've provided, play around and break things - that's the best way to learn.</li> </ul> <h3>Code/Environment Setup</h3> <p>In order to try out the code snippets or complete to-do tasks mentioned in each section, you can use <a href="https://colab.research.google.com/" target="_blank" rel="noopener">Google Colaboratory notebook</a>. Colab is basically Google's implementation of Jupyter Notebooks where you can run your code.</p> <p>You can learn more about working with Colabs by following <a href="https://colab.research.google.com/notebooks/intro.ipynb" target="_blank" rel="noopener">this notebook</a>.</p> </div>