![]() ![]() ![]() Jupyter Notebook installation and configuration While Notebook supports multiple languages (like R, Julia), we’ll be using Python (specifically, Python 3). Jupyter Notebook is a popular data science platform for analyzing, processing, classifying, modeling, and visualizing data. We will be using Jupyter Notebook for the signal processing and machine learning portion of our course. Step 2: Open Jupyter Notebook and configure extensions.Step 1: Use conda to install nbextensions.Jupyter Notebook installation and configuration. ![]() L4: Feature Selection and Hyperparameter Tuning.Follow the instructions below with default settings (Yes or Next). 64-Bit Graphical Installer for Windows) at and install it (Anaconda3-2021.11-Windows-x86_64.exe).This will be covered when it is necessary.Ī whole process of installing Python is as follows.ĭownload the recent Anaconda (Python 3.9 But, for the time being, it is not necessary. This approach helps you avoid version conflicts. Python programming is usually done with user-defined virtual environments which are constructed with some specific version of Python or Tensorflow. Instead, I use Google Colab when GPU Tensorflow is necessary. This post only deal with CPU version since my laptop does not have GPU and I can’t test it. Tensorflow is of two kinds : CPU and GPU version. Next we modify the default directory for Jupyter Notebook for our working directory. Without Anaconda, we need to install Python and lots of package manually.Īfter installing Anaconda, Tensorflow is installed since Anaconda does not contain Tensorflow. sklearn, pandas and so on) are installed automatically. It is common to use Anaconda for installing Python since a variety of packages (i.e. This post explains the an installation of Python, Tensorflow and configuration of Jupyter notebook as a kickstart towards ML/DL modeling. For a machine or deep learning modeling, Python is widely used with Tensorflow. ![]()
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