But WHY. Because it increases:. Efficiency: Reduces the need for large datasets for every new task.

But WHY? Because it increases🔼: ✅Efficiency: Reduces the need for large datasets for every new task ✅Flexibility: Can be applied to various learning problems, from classification to regression to reinforcement learning. 8/10

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We at @real_alethea are dedicated to democratizing ownership of AI, and true democratization cannot happen without AI Literacy. Follow @real_alethea for more on AI and Web3!🔔 RT 🔁to share it with your friends and Bookmark this for the future. 10/10
We at @real_alethea are dedicated to democratizing ownership of AI, and true democratization cannot happen without AI Literacy.
We at @real_alethea are dedicated to democratizing ownership of AI, and true democratization cannot happen without AI Literacy. Follow @real_alethea for more on AI and Web3!🔔 RT 🔁to share it with your friends and Bookmark this for the future. 10/10
Is it really all rainbows and unicorns?🌈🦄 No! There are some problems like high computational costs and overfitting. But @awscloud offers services like SageMaker to solve that. Learn more about how we're using AWS's services here: /AWSstartups/status/1709618705099850191?s=20 9/10
Is it really all rainbows and unicorns. There are some problems like high computational costs and overfitting.
Is it really all rainbows and unicorns?🌈🦄 No! There are some problems like high computational costs and overfitting. But @awscloud offers services like SageMaker to solve that. Learn more about how we're using AWS's services here: /AWSstartups/status/1709618705099850191?s=20 9/10