Neural Networks and Random Forests

Aperçu

Embark on a journey to master advanced AI techniques with our comprehensive course on Neural Networks and Random Forests, offered exclusively through Coursera. This curriculum is meticulously designed for individuals keen on expanding their knowledge beyond basic models, delving into the intricacies of artificial intelligence.

Our structured learning path begins with an in-depth exploration of neural networks.

Participants will start from the basics, understanding the structure and properties, before advancing to coding simple models themselves. The course emphasizes practical skills, such as avoiding overfitting through regularization and fine-tuning hyper-parameters.

Following this, you'll undertake a challenging project on predicting the likelihood of heart disease based on various health characteristics, employing the neural network models you’ve learned.

Transitioning from neural networks, the course shifts focus to random forests.

Here, students will appreciate the distinctions between these methodologies, exploring their unique origins and how they're applied in the field of artificial intelligence.

The concluding project revolves around employing random forests to predict similarities between health patients, integrating both theory and practical application.

This course, rich in content across multiple domains, forms part of several categories, including Artificial Intelligence, Python, Machine Learning, Neural Networks, TensorFlow, and Keras. Dive deep into these cutting-edge technologies and elevate your expertise with us on Coursera.

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Enseigné par

Rajvir Dua and Neelesh Tiruviluamala

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