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An Initiation to Deep Learning

This repo has been set up to show my journey through Deep Learning. It is meant to be used as a guide for a self-taught process. The different concepts will be discussed in a progessive manner, inorder to build necessary skills in the area.

I. TensorFlow

Google Colab: An easy way to learn and use TensorFlow. Google Colab is probably your best friend when learning TensorFlow. No install necessary—run the TensorFlow tutorials directly in the browser with Colaboratory, a Google research project created to help disseminate machine learning education and research. It's a Jupyter notebook environment that requires no setup to use and runs entirely in the cloud. Read the blog post. I could not find better introduction to the topic that the material available here. I called it The TensorFlow Notebooks. At the beginning, it assumes a familiarity with Numpy and really gives you the necessary to quick start with TensorFlow and Keras. I divided the work in a series of notebooks (each to be completed daily, ideally) I deemed suitable for a learner/beginner who wants to learn in a progressive way. However, feel free to move faster if your learning rate requires so.

I.1- Eager execution. Run the notebook locally by downloading it or even better run it in Colab

I.2- Introduction to Tensors. Run the notebook locally by downloading it or even better run it in Colab.

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