Neural networks have a lot of knobs and dials that you need to set correctly to get the best possible performance out of them. While some of them are self-explanatory and easy to understand (such as the number of neurons in the input layer) and can be chosen, there are many hyperparameters that are a bit more complex in terms of how they affect the outcome of the model (for example, the number of layers , the batch size or the weight initialization).

In this lesson we will look at the number of neurons in the input, output and hidden layers and the number of hidden layers. We will learn the rules and best practices for determining the number of hidden layers and the number of neurons within them.

Previous lesson: https://youtu.be/r2TvNmAxiCU
Next lesson: https://youtu.be/KI5gOnlQeN8

Here you will find a lesson notes booklet that summarizes everything you learn in this course in diagrams and visualizations. You can get it here https://misraturp.gumroad.com/l/fdl

NNs hyperparameters cheat sheet: https://www.soyouwanttobeadatascientist.com/nn-hyperparameters-cheat-sheet

‍ You can access all the code I develop in this course here: https://github.com/misraturp/Deep-learning-course-repo

To get the most out of the course, don't forget to answer the questions at the end of the module:
https://fishy-dessert-4fc.notion.site/Deep-Learning-101-Questions-35797462583d43a3adcea9478bfe035d

You can find the answers here:
https://fishy-dessert-4fc.notion.site/Deep-Learning-101-Answers-f90449595add492fb9dd8db3859662e3

SOURCES:
‍️ Data Science Kickstarter Mini Course: https://misraturp.gumroad.com/l/kick-starter
The cheat sheet for pandas: https://misraturp.gumroad.com/l/pandascs
Streamlit Template (updated 2023, now for 5): 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:
‍ Practical Data Science: Complete Your First Portfolio Project: https://www.misraturp.com/hods

Website – https://misraturp.com/
Twitter – https://twitter.com/misraturp

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