{"id":13659832,"url":"https://github.com/ajaybhat/Tensorflow-For-Beginners","last_synced_at":"2025-04-24T15:31:00.837Z","repository":{"id":72654680,"uuid":"94511861","full_name":"ajaybhat/Tensorflow-For-Beginners","owner":"ajaybhat","description":"Introduction to deep learning with Tensorflow. 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Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google's Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well.\" \n\n\n\u003ca href=https://github.com/ajaybhat/Tensorflow-101/blob/master/1.%20HelloWorld.ipynb\u003eHello World!\u003c/a\u003e\n\n\u003ccode\u003eimport tensorflow as tf\u003c/code\u003e\n\n\u003ccode\u003ewith tf.Session() as sess:\u003c/code\u003e\n\n\u003ccode\u003e        print(sess.run(tf.constant('Hello World!')))\u003c/code\u003e\n\n### Installing Conda\nAnaconda is available for Windows, Mac OS X, and Linux. You can find the installers and installation instructions at \u003ca href=\"https://www.continuum.io/downloads\" target=\"_blank\" data-unsp-sanitized=\"clean\"\u003ehttps://www.continuum.io/downloads\u003c/a\u003e\nIf you already have Python installed on your computer, this won't break anything. Instead, the default Python used by your scripts and programs will be the one that comes with Anaconda. Choose the Python 3.5 version. After installation, you’re automatically in the default conda environment with all packages installed which you can see below. You can check out your own install by entering \u003ccode\u003e conda list \u003c/code\u003e\n\nFrom your terminal, type: \n\u003ccode\u003e conda upgrade conda \u003c/code\u003e\n\n\u003ccode\u003e conda upgrade --all \u003c/code\u003e\n\n### Jupyter Notebooks\nThe Jupyter notebook is a web application that allows you to combine explanatory text, math equations, code, and visualizations all in one easily sharable document. \n\nBy far the easiest way to install Jupyter is with Anaconda. Jupyter notebooks automatically come with the distribution. You'll be able to use notebooks from the default environment.\n\nTo install Jupyter notebooks in a conda environment, use \u003ccode\u003e conda install jupyter notebook \u003c/code\u003e.\n\nJupyter notebooks are also available through pip with \u003ccode\u003e pip install jupyter notebook \u003c/code\u003e.\nTo open Jupyter notebook, Run the following from the root directory of your repository to open up a notebook:\n\u003ccode\u003ejupyter notebook\u003c/code\u003e\n\n### Installing dependencies\n\n\u003ccode\u003e conda install --yes --file requirements.txt\u003c/code\u003e\n\nThanks to Udacity and tensorflow.org for text and code samples.\n\n__Please submit a pull request if you'd like to see any changes or additions in this repo.__\n","funding_links":[],"categories":["Jupyter Notebook"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajaybhat%2FTensorflow-For-Beginners","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fajaybhat%2FTensorflow-For-Beginners","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fajaybhat%2FTensorflow-For-Beginners/lists"}