Batch Normalization | How does it work, how to implement it (with code)

Curious about deep learning? Start with the Fundamentals of Deep Learning booklet to learn the essentials in 25 pages - https://misraturp.gumroad.com/l/fdl 💪 Want to become a deep learning buff? 👇 Watch my full course on deep learning on YouTube https://youtube.com/playlist?list=PLM8lYG2MzHmQn55ii0duXdO9QSoDF5myF Batch normalization is the secret weapon that solves the unstable gradients problem for many of the Deep Learning architectures. Let's take a look into how batch normalization works under the hood, what other benefits it has and how we can implement it using Keras on a Jupyter Notebook. RESOURCES: Data Science Kick-starter mini-course: https://www.misraturp.com/courses/data-science-kick-starter-mini-course Pandas cheat sheet: https://misraturp.gumroad.com/l/pandascs Streamlit template: https://misraturp.gumroad.com/l/stemp NNs hyperparameters cheat sheet: https://www.misraturp.com/nn-hyperparameters-cheat-sheet Fundamentals of Deep Learning in 25 pages: https://misraturp.gumroad.com/l/fdl COURSES: Hands-on Data Science: Complete your first portfolio project: https://www.misraturp.com/hods Website - https://misraturp.com/ Twitter - https://twitter.com/misraturp