TensorFlow Tutorial For Beginners – Hacker Noon

Deep learning is a subfield of machine learning that is a set of algorithms that is inspired by the structure and function of the brain. TensorFlow is the second machine learning framework that Google created and used to design, build, and train deep learning models.You can use the TensorFlow library do to numerical computations, which in itself doesn't seem all too special, but these computations are done with data flow graphs. In these graphs, nodes represent mathematical operations, while the edges represent the data, which usually are multidimensional data arrays or tensors, that are communicated between these edges. The name "TensorFlow" is derived from the operations which neural networks perform on multidimensional data arrays or tensors! For now, this is all you need to know about tensors, but you'll go deeper into this in the next sections! Today's TensorFlow tutorial for beginners will introduce you to performing deep learning in an interactive way: Also, you could be interested in a course on Deep Learning in Python, DataCamp's Keras tutorial or the keras with R tutorial. To understand tensors well, it's good to have some working knowledge of linear algebra and vector calculus. You already read in the introduction that tensors are implemented in TensorFlow as multidimensional data arrays, but some more introduction is maybe needed in order to completely grasp tensors and their use in machine learning.