One hot encoding approach is used to encode category data as numerical variables. It is also known as "dummy encoding" or "one-of-K encoding." The procedure entails establishing a new binary variable for each category in the categorical variable. This can be beneficial in machine learning and data analysis when working with categorical variables that do not have a natural order or ranking. When is it appropriate to execute one hot encoding? One hot encoding is appropriate for usage when the categorical variable is not ordinal, which means the categories do not have a natural order or ranking. It is also beneficial when the category variable has numerous levels or categories. For example, a variable with the levels "red", "green", and "blue" would be a good candidate for one hot encoding. One popular top category encoding When working with huge datasets, encoding all levels of a category variable with a single hot might result in a sign
Hello there and welcome As the title suggests this post is about updating you GPU driver(Nvidia) and updating Anaconda to be able to use GPU with tensorflow(or any other) Let's start first off go to search bar and type Geforce Experience then open that applications If u have a nvidia Gpu card but don't have that driver go to https://www.nvidia.com/en-us/geforce/geforce-experience/ to download it Then go to Drivers and if the update is available it should so something like this Go ahead and update after downloading be sure to install it Next is to upgrade conda(Anaconda) be sure that when we are installing GPU support in tensorflow we will be using virtual enviroment for doing so Open up powershell as admin mode You can either go to Search bar and type powershell, right click it then click start as administrator or press windows_key +x and then press a then type conda update conda This is is to prepare your graphics driver and conda for it