✅ Hierarchical Multi-label Classification

✳️ Multi-label classification is a standard machine learning problem in which an object can be associated with multiple labels. A hierarchical multi-label classification (HMC) problem is defined as a multi-label classification problem in which classes are hierarchically organized as a tree or as a directed acyclic graph (DAG), and in which every prediction must be coherent, i.e., respect the hierarchy constraint. The hierarchy constraint states that a datapoint belonging to a given class must also belong to all its ancestors in the hierarchy.

✅ paper
🔗 Github

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People have already started building awesome apps on top of #ChatGPT

Here are 10 use cases ChatGPT liked the most.

1. 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐲𝐨𝐮𝐫 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮𝐫 𝐖𝐡𝐚𝐭𝐬𝐚𝐩𝐩.

2. 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐖𝐫𝐢𝐭𝐞𝐫: It use ChatGPT to generate emails or replies based on your prompt!

3. 𝐖𝐞𝐛𝐂𝐡𝐚𝐭𝐆𝐏𝐓: gives you relevant results from the web!

4. 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐒𝐮𝐦𝐦𝐚𝐫𝐲 𝐰𝐢𝐭𝐡 𝐂𝐡𝐚𝐭𝐆𝐏𝐓: It generate text summaries of any YouTube video!

5. 𝐓𝐰𝐞𝐞𝐭𝐆𝐏𝐓: It uses ChatGPT to write your tweets, reply, comment, etc.

6. 𝐒𝐞𝐚𝐫𝐜𝐡 𝐆𝐏𝐓: It display the ChatGPT response alongside Google Search results

7. 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐨𝐫 𝐚𝐥𝐥 𝐬𝐞𝐚𝐫𝐜𝐡 𝐞𝐧𝐠𝐢𝐧𝐞𝐬: You can now view ChatGPT responses on Google and Bing!

8. 𝐒𝐚𝐯𝐞 𝐚𝐥𝐥 𝐲𝐨𝐮𝐫 𝐏𝐫𝐨𝐦𝐩𝐭𝐬: The ChatGPT History extension has you covered!

9. 𝐑𝐞𝐦𝐚𝐤𝐞 𝐚 𝐯𝐢𝐝𝐞𝐨: Just pick a video you liked and visit to get its transcript. Once done, bring that back to Chat GPT and tell it to summarize the transcript. Read the summary and make a video on that yourself.

10. 𝐒𝐞𝐚𝐫𝐜𝐡 𝐰𝐡𝐚𝐭 𝐩𝐞𝐨𝐩𝐥𝐞 𝐚𝐫𝐞 𝐏𝐫𝐨𝐦𝐩𝐭𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐅𝐥𝐨𝐰𝐆𝐏𝐓

#آموزش

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