Neural Networks for Machine Learning | Neural Networks Explained | Scikit Learn|Datacode with Sharad

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⭐️Neural networks for machine learning are computational models inspired by the structure and function of the human brain. They consist of interconnected nodes (neurons) organized into layers. Information is processed through these layers using weighted connections, and the network learns to make predictions or classifications by adjusting these weights based on input-output pairs during training. Neural networks are a fundamental component of deep learning and have shown remarkable success in tasks such as image and speech recognition, natural language processing, and various other machine learning applications.

Neural Networks for Machine Learning | Neural Networks Explained | Scikit Learn|Datacode with Sharad
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[b_.techian_trader]

Once again Awesome lecture ❤❤❤❤❤❤❤❤❤❤❤❤❤

[imdadullah]

Thank you so much sir. I understand easily concept of all machine learning algorithms and neutral network🎉❤.

[prakashkumar-eehy]

Sir I found many this topic but not i get it Finally you upload Pass or fail exam predicting Supervised Thankuu 🤗

[harshaddeshmukh]

Sir, yaha neural network me data ki testing kyu nhi ki humne? train_test_split use nhi Kiya aisa kyu?

[imdadullah]

Pl make a video deep learning and Ai generative.