![]() The Deep Learning module of our Data Scientist training course covers TensorFlow, KERAS and the CNN and RNN neural networks. To learn how to use it, you can choose DataScientest training courses. In the event of an error, please check that you have followed the instructions correctly.Īs a key Machine Learning tool, TensorFlow is indispensable in Data Science. The new environment you’ve just installed and configured is ready for development with tensorflow. Hello = tf.constant (‘Hello, TensorFlow! ‘) Select “Open with IPython”, and a terminal window appears with the environment parameters.įollowing the recommendations on the official Tensorflow website, type this command in the terminal window: Make sure it is selected, then click on the arrow next to the Tensorflow environment name. Click on Apply.Īll that remains is to validate the installation using the new Tensorflow environment. Check the box in the left-hand column next to the two tensorflow package names. Type “tensorflow” in the Search Packages text field and click Return. In the top-right drop-down menu, select “Not Installed”. The Tensorflow packages can now be installed in the new environment. Check the Python box, and select the latest version. In the menu that opens, type “Tensorflow” in the “Name” text field. The latest version of Python and Tensorflow will be installed.Ĭlick on the “Create” button at the bottom of the Environments column. This environment will contain the basic packages required. A new environment can be created to install TensorFlow packages.
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