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Setup Mac for Machine Learning with TensorFlow in 13 minutes (works for all M1, M2)
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Setup your Apple M1 or M2 (Normal, Pro, Max or Ultra) Mac for data science and machine learning with TensorFlow.
In this video, we install Homebrew and Miniforge3 to create a Conda environment containing pandas, NumPy, Scikit-Learn, Matplotlib, Jupyter and TensorFlow.
We'll also setup TensorFlow to leverage the GPU on the new M1 chips.
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Timestamps:
0:00 - Intro
0:30 - What we're covering
1:00 - All resources are on GitHub
1:25 - Downloading and installing Homebrew
2:45 - Downloading and installing Miniforge3
4:25 - Restart terminal for changes to take effect
4:57 - Creating a directory to test out TensorFlow
5:30 - Creating a Conda environment for machine learning experiments
7:12 - Installing TensorFlow dependencies for Mac from Apple's Conda channel
8:40 - Installing tensorflow-macos
9:15 - Installing tensorflow-metal so you can run TensorFlow on your Mac's GPU
10:30 - Installing tensorflow-datasets (optional)
10:50 - Installing standard data science packages (Jupyter, NumPy, pandas, Matplotlib, Sklearn)
11:15 - Starting a Jupyter Notebook
11:40 - Testing importing different libraries and seeing if TensorFlow has GPU access
#MachineLearning #MacBookPro
In this video, we install Homebrew and Miniforge3 to create a Conda environment containing pandas, NumPy, Scikit-Learn, Matplotlib, Jupyter and TensorFlow.
We'll also setup TensorFlow to leverage the GPU on the new M1 chips.
Links:
Connect elsewhere:
Timestamps:
0:00 - Intro
0:30 - What we're covering
1:00 - All resources are on GitHub
1:25 - Downloading and installing Homebrew
2:45 - Downloading and installing Miniforge3
4:25 - Restart terminal for changes to take effect
4:57 - Creating a directory to test out TensorFlow
5:30 - Creating a Conda environment for machine learning experiments
7:12 - Installing TensorFlow dependencies for Mac from Apple's Conda channel
8:40 - Installing tensorflow-macos
9:15 - Installing tensorflow-metal so you can run TensorFlow on your Mac's GPU
10:30 - Installing tensorflow-datasets (optional)
10:50 - Installing standard data science packages (Jupyter, NumPy, pandas, Matplotlib, Sklearn)
11:15 - Starting a Jupyter Notebook
11:40 - Testing importing different libraries and seeing if TensorFlow has GPU access
#MachineLearning #MacBookPro
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