AI Code Explainer in Python - Discover how to create an AI code explainer using Python. Learn the techniques and libraries needed to implement this innovative solution.
Step up your coding game with AI-powered Code Explainer. Get insights like never before! In this tutorial, we will make a simple maths game on the console with the PyInputPlus module. The main features of this simple game are adding points (like a score), multiple equation types (such ...
Unlock the secrets of your code with our AI-powered Code Explainer. Take a look!YouTube is a great platform where you can find tons of great video resources, be it programming, entrepreneurship, movies, etc. It is a platform that also enables users to live stream and watch videos online....
(x_test) # if you used the PFIExplainer in the previous step, use the next line of code instead # global_explanation = explainer.explain_global(x_train, true_labels=y_train) # sorted feature importance values and feature names sorted_global_importance_values = global_explanation.get_ranked...
Therefore, I can simply load it using the below code:from datasets import load_dataset # load the custom dataset ds = load_dataset("imagefolder", data_dir="data") ds CopyExploring the DatasetGoing back to the food101 dataset. Here's the output of ds:...
Alternatively, you can also run the code in a new Jupyter Notebook (which comes with Anaconda). Step 3: Import libraries and modules. Let’s start by importing numpy and setting a seed for the computer’s pseudorandom number generator. This allows us to reproduce the results from our ...
Keep the learning going with our AI-powered Code Explainer. Try it now! View Full Code Analyze My Code Sharing is caring! Read Also How to Build an Authentication System in Django Learn how you can build a simple authentication system (sign up, login, and logout) using the Django ...
thonny-error-explainerextends Assistant with new error checkers thonny-lahendusallows loading exercises fromlahendus.ut.eeand submitting solutions for automatic assessment. thonny-edisonallows uploading Python code toEdison educational robot thonny-draculaadds Dracula syntax theme. ...
shap_values=explainer.shap_values(pd.concat([train_x,test_x])) shap.summary_plot(shap_values[1],pd.concat([train_x,test_x]),max_display=5,plot_size=(5,5))#特征重要性可视化 1. 2. 3. 4. 5. 6. 其他模型可解释性框架 LIME
TheBlitz Introduction to DGLis a 120-minute tour of the basics of graph machine learning. TheUser Guideexplains in more details the concepts of graphs as well as the training methodology. All of them include code snippets in DGL that are runnable and ready to be plugged into one’s own ...