A Review of Hyperparameter Tuning Techniques for Neural Networks

👇 Watch my full course on deep learning on YouTube

Let's look into the commonly used hyperparameter tuning techniques for Neural Networks in this video.

We will look into Grid search, Random search, Manually zooming in and some other sophisticated techniques such as Bayesian search, gradient-based search and evolutionary algorithms.

Here are the libraries that implement some of these techniques:

RESOURCES:

COURSES:

[misraturp]

🤔 Curious about deep learning?
Start with the Fundamentals of Deep Learning booklet to learn the essentials in 25 pages

[secondaryvegetationjuggern]

Why am I only discovering this now 😢 For non-native English speakers like me, this is very helpful because you speak clearly on each words. In addition, the explanations are easy to understand

[rafikabenledghem]

It just about what I was looking for, thnx a lot you're just amazing

[hsoley]

Another great Video Misra! keep them coming!

[danja]

Great introduction to hyperparam tuning - thank you! Do you have any tipps or articles about hyperparam tuning in Nuronal Networks for Time Series problems?

[magedsaeed]

Thanks for this talk. I wonder why ray is not mentioned as an industry standard solution for tuning and distributed computing in general.

[Leo-wkpy]

thanks, great video. when you have time share your knowledge.

[debojitmandal]

hi mam your beautiful altough i came to study here but i thought of letting u know this