Introduction to Neural Networks Bootcamp
Introduction to Neural Networks These state-of-the-art methods build powerful predictive systems and find latent patterns in large amounts of data. By the end of this course, students will learn the foundations of this complex topic and acquire practical skills to build neural networks in order to solve real-world problems. Objectives: Define powerful applications and use cases that incorporate deep learning. Build foundational neural network models. Implement best practices on deep learning models Any student in this program must have a strong foundation in Python and the common libraries: SciKit-Learn, Pandas, NumPy, and Matplotlib. Additionally, students should have a foundational knowledge of statistics, unsupervised machine learning algorithms, and classification algorithms.
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