 Hello everyone! I hope you all are doing well. Artificial intelligence is gaining popularity day by day and the most fascinating is natural language processing, using which robots can understand the languages spoken by humans. Not only understand but also feel the emotions behind it. Isn't it amazing? In this video, we are going to try our hands-on on the latest NLP extension of picture blocks by making virtual doctor. You just need to tell your symptoms and he will tell you what caught you and what you should do next. Along with the NLP extension, there are a lot of new features added to the latest version of picture blocks. If you haven't downloaded it yet, you can download it from the link given in the description box below or the card above. Let's begin! Open picture blocks. First of all, let's add the doctor and the hospital's sprite and set up the stage. You can download these sprites from the link given in the description box. Once downloaded, you can place them as per your choice or like the type we have placed here. Next, add the NLP extension. NLP stands for natural language processing. This is the area of AI concerned with the interaction between computers and humans in natural language. The aim of this extension is to help computers understand language as well as we do. Now, we need to train picture blocks to analyze the text and perform the corresponding actions. For training, we will add data of symptoms for three diseases, that is COVID-19, malaria and diabetes, one by one. Go to the My Blocks palette and create a block named Data for COVID-19. To add data to the text classifier, we need the NLP extension. Take an add class block and place it below the hat block. In place of text, write the first symptom, dry cough and write COVID-19 as class. Let's add more symptoms to COVID-19 class. You can add as many as you may find. Only thing you need to do is just duplicate the block and write the symptoms you want to add. Now, similarly, add data for the other two diseases. We'll add three symptoms for each. Now, we need to train our text classifier. Create a block named Training. Take the training hat block and add a reset text classifier block below it. Add the data for COVID-19, data for malaria and data for diabetes tag blocks one after the other. Add a train text classifier block. Next, let's begin to write the script to make the virtual doctor say the name of the disease we have after we tell him our symptoms. Add a when flag clicked hat block. Drop the train data stack block below it. Let's make the doctor greet us. Add a save block. Write, hello, welcome to the virtual hospital. Next, we'll warn the doctors to ask the symptoms. Thus, from the sensing palette, add a ask and wait block. Write, how are you feeling today? Please tell me your symptoms. Here is when we will try the symptoms and the doctor will tell us the remedies for the same. Place enough block into the scripting area. Add an equal to block from the operator's palette. Inside the first space of the equal to block, drop a get class of block. In the second space, write COVID-19. Inside the get class of block, drop an answer block from the sensing palette. This will check the symptoms you enter and if they match with COVID class, the doctor will say out the disease as COVID-19. Into the if arm, place a save block and write you are infected with COVID-19. Now that we know the disease, the doctor will say the remedy for the same. Place a save block from the looks palette and write remedies into it. If you need to write more remedies, you can use another save block too. Similarly, we will do malaria and diabetes. Duplicate the if block and make the changes respectively. This, our script is complete. Press the green flag to start the script. Let's test and write the symptom as I am feeling breathless and have been experiencing fever. Yes, head got detected correctly. To escalate the project, instead of typing your symptoms, you can use speech recognition blocks to recognize your voice and then diagnosis. So this is all from my side. Now it's your turn to make this project. But don't forget to share this project with the Pictoblocks community on Facebook, which you can join from the link given in the description box below. If you like this project, give it a thumbs up and subscribe to Stempedia. Stay safe, stay healthy. Bye bye.