How to Install Tensorflow 2.0 on Mac Or Linux?

9 minutes read

To install TensorFlow 2.0 on a Mac or Linux system, you can use either pip or Anaconda to install the package. First, ensure that you have Python 3.5 or later installed on your system.


To install TensorFlow using pip, open a terminal and run the following command:

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pip install tensorflow


If you prefer using Anaconda, you can create a new environment and install TensorFlow by running the following commands:

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conda create -n tf_env
conda activate tf_env
conda install tensorflow


After installation, you can verify the installation by importing TensorFlow in a Python script or a Jupyter notebook and running a simple computation to ensure everything is working correctly.

Best TensorFlow Books of July 2024

1
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

2
Machine Learning Using TensorFlow Cookbook: Create powerful machine learning algorithms with TensorFlow

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Advanced Natural Language Processing with TensorFlow 2: Build effective real-world NLP applications using NER, RNNs, seq2seq models, Transformers, and more

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Hands-On Neural Networks with TensorFlow 2.0: Understand TensorFlow, from static graph to eager execution, and design neural networks

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Machine Learning with TensorFlow, Second Edition

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TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning

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Hands-On Computer Vision with TensorFlow 2: Leverage deep learning to create powerful image processing apps with TensorFlow 2.0 and Keras

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TensorFlow 2.0 Computer Vision Cookbook: Implement machine learning solutions to overcome various computer vision challenges

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What is the minimum system requirements for installing TensorFlow 2.0 on Mac?

The minimum system requirements for installing TensorFlow 2.0 on Mac are as follows:

  • MacOS 10.12.6 (Sierra) or later
  • Python 3.5, 3.6 or 3.7
  • pip package manager
  • CUDA (if using GPU support)
  • cuDNN (if using GPU support)


How to install TensorFlow 2.0 on Linux with GPU support?

To install TensorFlow 2.0 on Linux with GPU support, you can follow the steps below:

  1. Check if you have a compatible GPU by installing the nvidia-smi tool and running the command nvidia-smi in the terminal. This will show you information about your GPU.
  2. Install CUDA Toolkit by following the instructions on the NVIDIA website: https://developer.nvidia.com/cuda-toolkit
  3. Install cuDNN by downloading the cuDNN library from the NVIDIA website (you may need to create an account) and following the installation instructions provided.
  4. Create a virtual environment (optional but recommended) by using a tool like virtualenv or conda.
  5. Install TensorFlow 2.0 with GPU support using pip:
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pip install tensorflow-gpu


  1. Verify that TensorFlow is using the GPU by running the following code in a Python script or a Jupyter notebook:
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import tensorflow as tf
print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))


If everything is set up correctly, you should see the number of GPUs available printed out.


That's it! You have successfully installed TensorFlow 2.0 with GPU support on Linux.


How to install TensorFlow 2.0 on Mac using Anaconda?

To install TensorFlow 2.0 on a Mac using Anaconda, follow these steps:

  1. First, install Anaconda if you haven't already. You can download Anaconda from the official website and follow the installation instructions.
  2. Open a terminal window.
  3. Create a new conda environment by running the following command:
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conda create -n tf_env python=3.7


This will create a new environment called "tf_env" with Python version 3.7. You can change the Python version if needed.

  1. Activate the new environment by running the following command:
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conda activate tf_env


  1. Install TensorFlow 2.0 by running the following command:
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pip install tensorflow


  1. You can also install additional packages that you may need for your TensorFlow projects, such as NumPy, Matplotlib, or Jupyter:
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pip install numpy matplotlib jupyter


  1. Verify the installation by importing TensorFlow in a Python script or Jupyter notebook:
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import tensorflow as tf
print(tf.__version__)


This should print the version of TensorFlow that you have installed.


That's it! You have successfully installed TensorFlow 2.0 on your Mac using Anaconda. You can now start building and training machine learning models using TensorFlow.


How to install TensorFlow 2.0 on Linux using apt-get?

You can install TensorFlow 2.0 on Linux using the following steps:

  1. Update your package list and install the required dependencies:
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sudo apt update
sudo apt install python3-dev python3-pip


  1. Install TensorFlow using pip:
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pip install tensorflow


Alternatively, you can install TensorFlow using apt-get for faster installation and optimization for your hardware. Here's how to do it:

  1. Add the TensorFlow repository to your package sources:
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echo "deb [arch=amd64] http://storage.googleapis.com/tensorflow-serving-apt stable tensorflow-model-server tensorflow-model-server-universal" | sudo tee /etc/apt/sources.list.d/tensorflow-serving.list


  1. Add the TensorFlow public key:
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curl https://storage.googleapis.com/tensorflow-serving-apt/tensorflow-serving.release.pub.gpg | sudo apt-key add -


  1. Update your package list and install TensorFlow:
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sudo apt update
sudo apt install tensorflow


This will install TensorFlow 2.0 on your Linux system using apt-get.

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