Let's move to the next step, which is to install the Jupyter notebook software. If python is installed correctly then you should able to see the python version number and some key help, as shown below in Fig 6. Let's test if python installed successfully, open command prompt and type "python". Installation will complete in a minute or two. We have created 'Python' folder in C drive in earlier step (Fig 2) Fig 5: choose the location I followed the customization method to avoid setting up environment variable.Īs below figure 5 shown, the Customize installation location, where make sure you put the installation location folder C:\Python\Python39. Make sure to choose 'Customize Installation' and check mark 'Add Python 3.9 to PATH' as shown in figure 4. Now double click the executable file to initiate the installation process. Now next step is to create a 'Python' folder under the C: drive, we will use this folder as installation location at later step.įind out the downloaded executable file, I have saved the executable file under Downloads folder (shown in below figure 3). You can download the executable file and save in any location at your computer. Please choose the version as per your computer Operating system. I have chosen 'Windows x86-64 executable installer' for my Windows 64 bit OS. Please follow this URL and choose right version to install. Python is a prerequisite for running a Jupyter notebook, so we need to install python first. This post will describe the step by step installation process of Jupyter notebook. The Jupyter Notebook can be used for data cleaning and transformation, data visualization, machine learning, statistical modeling and much more. Well, that's how I found a Jupyter notebook can be useful to compare two. At the beginning I was manually comparing them then I thought there must be a tool to do that. parquet were created from two different sources, the outcome should be completely alike, schema wise. This is mainly a schema comparison, not a data comparison. One of the projects I was working required a comparison of two parquet files. Follow the instructions below with default settings (Yes or Next).Whether you work as a Data Engineer or a Data Scientist, a Jupyter Notebook is a helpful tool. 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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